Datasets:

ShushengYang

/

rel_dir_ctr_gen_miniset

like 0

arkitscenes

42444976

object_rel_direction_v1

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['refrigerator', 'table', 'dishwasher'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

front-left

A

.mov

241009

refrigerator

table

dishwasher

arkitscenes

42446167

object_rel_direction_v1

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['table', 'bed', 'toilet'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

back-left

A

.mov

241009

table

bed

toilet

arkitscenes

45261121

object_rel_direction_v1

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['table', 'stool', 'tv'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

front-right

B

.mov

241009

table

stool

tv

arkitscenes

47204552

object_rel_direction_v1

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['stove', 'tv', 'table'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

front-right

B

.mov

241009

stove

tv

table

arkitscenes

47331970

object_rel_direction_v1

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['refrigerator', 'table', 'dishwasher'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

front-left

C

.mov

241009

refrigerator

table

dishwasher

arkitscenes

47333899

object_rel_direction_v1

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['refrigerator', 'table', 'washer'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

back-left

C

.mov

241009

refrigerator

table

washer

arkitscenes

42445031

object_rel_direction_v2

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['tv', 'bed', 'table'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

right

A

.mov

241009

tv

bed

table

arkitscenes

42898527

object_rel_direction_v2

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['stove', 'dishwasher', 'refrigerator'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

right

A

.mov

241009

stove

dishwasher

refrigerator

arkitscenes

45260928

object_rel_direction_v2

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['tv', 'sofa', 'fireplace'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

left

B

.mov

241009

tv

sofa

fireplace

arkitscenes

47333899

object_rel_direction_v2

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['refrigerator', 'stove', 'table'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

left

A

.mov

241009

refrigerator

stove

table

arkitscenes

47334239

object_rel_direction_v2

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['bathtub', 'washer', 'stool'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

left

C

.mov

241009

bathtub

washer

stool

arkitscenes

47334239

object_rel_direction_v2

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['washer', 'bathtub', 'stool'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

right

C

.mov

241009

washer

bathtub

stool

arkitscenes

47430468

object_rel_direction_v2

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['stove', 'stool', 'refrigerator'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

right

B

.mov

241009

stove

stool

refrigerator

arkitscenes

42897688

object_rel_direction_v3

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['bed', 'stool', 'table'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

right

B

.mov

241009

bed

stool

table

arkitscenes

47331970

object_rel_direction_v3

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['dishwasher', 'refrigerator', 'table'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

left

A

.mov

241009

dishwasher

refrigerator

table

arkitscenes

47429922

object_rel_direction_v3

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['sofa', 'tv', 'chair'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

right

B

.mov

241009

sofa

tv

chair

scannetpp

acd95847c5

object_rel_direction_v2

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['door', 'bookshelf', 'laptop'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

left

A

.mp4

241009

door

bookshelf

laptop

scannetpp

a24f64f7fb

object_rel_direction_v2

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['monitor', 'computer mouse', 'door'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

right

C

.mp4

241009

monitor

computer mouse

door

scannetpp

5eb31827b7

object_rel_direction_v2

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['computer tower', 'telephone', 'keyboard'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

left

C

.mp4

241009

computer tower

telephone

keyboard

scannetpp

3864514494

object_rel_direction_v2

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['heater', 'door', 'microwave'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

right

B

.mp4

241009

heater

door

microwave

scannetpp

e398684d27

object_rel_direction_v2

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['door', 'ceiling light', 'monitor'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

left

C

.mp4

241009

door

ceiling light

monitor

scannetpp

286b55a2bf

object_rel_direction_v2

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['toilet', 'exhaust fan', 'door'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

left

B

.mp4

241009

toilet

exhaust fan

door

scannetpp

a980334473

object_rel_direction_v2

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['ceiling light', 'chair', 'door'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

right

A

.mp4

241009

ceiling light

chair

door

scannetpp

f2dc06b1d2

object_rel_direction_v2

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['chair', 'table', 'door'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

right

C

.mp4

241009

chair

table

door

scannetpp

bcd2436daf

object_rel_direction_v2

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['chair', 'pillow', 'ceiling light'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

right

C

.mp4

241009

chair

pillow

ceiling light

scannetpp

0d2ee665be

object_rel_direction_v2

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['door', 'cutting board', 'computer mouse'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

right

B

.mp4

241009

door

cutting board

computer mouse

scannetpp

5eb31827b7

object_rel_direction_v1

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['door', 'telephone', 'keyboard'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

front-left

B

.mp4

241009

door

telephone

keyboard

scannetpp

40aec5fffa

object_rel_direction_v1

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['refrigerator', 'heater', 'door'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

back-right

C

.mp4

241009

refrigerator

heater

door

scannetpp

3e8bba0176

object_rel_direction_v3

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['coat hanger', 'paper bag', 'door'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

left

B

.mp4

241009

coat hanger

paper bag

door

scannetpp

09c1414f1b

object_rel_direction_v3

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['shoe rack', 'microwave', 'kettle'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

right

A

.mp4

241009

shoe rack

microwave

kettle

scannet

scene0378_01

object_rel_direction_v1

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['window', 'clock', 'trash bin'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

front-right

B

.mp4

241009

window

clock

trash bin

scannet

scene0378_01

object_rel_direction_v1

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['window', 'trash bin', 'clock'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

front-left

A

.mp4

241009

window

trash bin

clock

scannet

scene0608_00

object_rel_direction_v1

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['sofa', 'lamp', 'guitar'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

front-left

A

.mp4

241009

sofa

lamp

guitar

scannet

scene0050_01

object_rel_direction_v1

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['printer', 'lamp', 'piano'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

front-left

B

.mp4

241009

printer

lamp

piano

scannet

scene0246_00

object_rel_direction_v1

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['nightstand', 'chair', 'table'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

front-right

B

.mp4

241009

nightstand

chair

table

scannet

scene0357_01

object_rel_direction_v3

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['window', 'table', 'towel'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

left

A

.mp4

241009

window

table

towel

scannet

scene0357_01

object_rel_direction_v3

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['towel', 'window', 'table'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

left

A

.mp4

241009

towel

window

table

scannet

scene0629_01

object_rel_direction_v3

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['bed', 'chair', 'mirror'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

left

B

.mp4

241009

bed

chair

mirror

scannet

scene0699_00

object_rel_direction_v3

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['chair', 'nightstand', 'closet'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

right

B

.mp4

241009

chair

nightstand

closet

scannet

scene0699_00

object_rel_direction_v3

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['nightstand', 'chair', 'closet'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

left

B

.mp4

241009

nightstand

chair

closet

scannet

scene0304_00

object_rel_direction_v2

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['backpack', 'trash bin', 'door'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

back

A

.mp4

241009

backpack

trash bin

door

scannet

scene0307_02

object_rel_direction_v2

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['refrigerator', 'chair', 'table'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

left

B

.mp4

241009

refrigerator

chair

table

scannet

scene0697_01

object_rel_direction_v2

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['mirror', 'closet', 'trash bin'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

left

B

.mp4

241009

mirror

closet

trash bin

scannet

scene0458_00

object_rel_direction_v2

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['window', 'door', 'towel'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

left

B

.mp4

241009

window

door

towel

scannet

scene0593_00

object_rel_direction_v2

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['backpack', 'fan', 'door'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

right

A

.mp4

241009

backpack

fan

door

scannet

scene0144_00

object_rel_direction_v2

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['lamp', 'printer', 'door'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

left

C

.mp4

241009

lamp

printer

door

scannet

scene0144_00

object_rel_direction_v2

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['window', 'lamp', 'door'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

right

C

.mp4

241009

window

lamp

door

scannet

scene0144_00

object_rel_direction_v2

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['lamp', 'window', 'door'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

left

A

.mp4

241009

lamp

window

door

scannet

scene0221_01

object_rel_direction_v2

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['microwave', 'nightstand', 'trash bin'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

right

C

.mp4

241009

microwave

nightstand

trash bin

scannet

scene0222_01

object_rel_direction_v2

[Task] This video captures an indoor scene. Your objective is to identify specific objects within the video, understand the spatial arrangement of the scene, and estimate the center point of each object, assuming the entire scene is represented by a 10x10 grid. [Rule] 1. We provide the cared categories: ['lamp', 'radiator', 'nightstand'] in this scene. Focus ONLY on these categories. 2. Estimate the center location of each instance within the provided categories, assuming the entire scene is represented by a 10x10 grid. 3. If a category contains multiple instances, include all of them. 4. Each object's estimated location should accurately reflect its real position in the scene, preserving the relative spatial relationships among all objects. [Output] Present the estimated center locations for each object as a list within a dictionary. STRICTLY follow this JSON format: {"category name": [(x_1, y_1), ...], ...}

back

B

.mp4

241009

lamp

radiator

nightstand