Upload 8 files

.gitattributes

@@ -34,3 +34,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
 SimHei.ttf filter=lfs diff=lfs merge=lfs -text
+examples/dubai.png filter=lfs diff=lfs merge=lfs -text
+examples/liuxiang.mp4 filter=lfs diff=lfs merge=lfs -text

examples/liuxiang.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:29e1448fe188d8cca2e85fd81c236c53fd61784063d93bc09e2301d33798937a
+size 26855609

examples/resume.md

@@ -0,0 +1,51 @@
+# Qidong Huang
+
+Building No.7, USTC West CampusHefei, Anhui, China
+
+Ph.D, University of Science and Technology of China
+
+H (+86) 13085060686
+
+B [email protected]
+
+# Short Biography
+
+Qidong Huang is a PhD student at University of Science and Technology of China. He has published more than 7 papers at top1-tier conferences and journals, such as CVPR/ICCV/AAAI/TIP/TCSVT. His research interests focus on vision transfer learning (e.g., prompt learning for vision pretrained models) and artificial intelligence security (e.g., adversarial examples and anti-DeepFake). He is the reviewer of many top conferences (including CVPR, ICCV, ECCV) and top journals (TNNLS, PR).
+
+# Education
+
+|09/2020–present|PhD of Cyberspace Security, University of Science and Technology of China, Hefei, China, CAS Key Laboratory of Electromagnetic Space Information. Supervised by Prof. Weiming Zhang.|
+|---|---|
+|09/2016–06/2020|Bachelor of Information Security, School of Information Science and Technology, University of Science and Technology of China, Hefei, China.|
+
+# Skills
+
+- Expertise in vision prompt learning: I have been researching the prompt learning for large-scale vision pretrained models and published one paper on top-tier computer vision conferences, in which I propose DAM-VP, a data diversity-aware method for efficient and adaptive vision prompt learning. This work alleviates the mismatch between vision prompts and downstream data diversity.
+- Expertise in artificial intelligence security: I have been studying artificial intelligence security since 2020, including adversarial attack&defense and anti-DeepFake. For adversarial attack, I propose SI-Adv, a shape-invariant attack for 3D point cloud recognition which great boosts the imperceptibility of adversarial examples. For adversarial defense, I propose a contrastive adversarial training framework for robust point cloud recognition named PointCAT. Besides, our work for improving adversarial robustness of masked autoencoders has been recently accepted by ICCV 2023. For anti-DeepFake, we are the first to propose the concept of “initiative defense” against DeepFakes by proactively protecting users’ facial privacy before the manipulation, unlike previous ex-post countermeasures like DeepFake detection.
+
+# Publications (First Author)
+
+Qidong Huang, Xiaoyi Dong, Dongdong Chen, Yinpeng Chen, Lu Yuan, Gang Hua, Weiming Zhang, Nenghai Yu. Improving Adversarial Robustness of Masked Autoencoders via Test-time Frequency-domain Prompting. International Conference on Computer Vision (ICCV), 2023.
+Qidong Huang, Xiaoyi Dong, Dongdong Chen, Weiming Zhang, Feifei Wang, Gang Hua, Nenghai Yu. Diversity-Aware Meta Visual Prompting. Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
+Qidong Huang, Xiaoyi Dong, Dongdong Chen, Hang Zhou, Weiming Zhang, Nenghai Yu. Shape-invariant 3D Adversarial Point Clouds. Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
+---
+# Publications
+
+Qidong Huang*, Jie Zhang*, Wenbo Zhou, Weiming Zhang, Nenghai Yu. Initiative Defense against Facial Manipulation. AAAI Conference on Artificial Intelligence (AAAI), 2021. (*Qidong Huang and Jie Zhang contribute equally.)
+Qidong Huang, Xiaoyi Dong, Dongdong Chen, Hang Zhou, Weiming Zhang, Kui Zhang, Gang Hua, Nenghai Yu. PointCAT : Contrastive Adversarial Training for Robust Point Cloud Recognition. IEEE Transactions on Image Processing (TIP), Major Revision.
+Kui Zhang, Hang Zhou, Jie Zhang, Qidong Huang, Weiming Zhang, Nenghai Yu. Ada3Diff : Defending against 3D Adversarial Point Clouds via Adaptive Diffusion. Under Review
+Han Fang, Dongdong Chen, Qidong Huang, Jie Zhang, Zehua Ma, Weiming Zhang* and Nenghai Yu. Deep Template-based Watermarking. IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2020.
+Jie Zhang, Dongdong Chen, Qidong Huang, Jing Liao, Weiming Zhang, Huamin Feng, Gang Hua, Nenghai Yu. Poison ink : Robust and invisible backdoor attack. IEEE Transactions on Image Processing (TIP), 2022.
+
+# Services
+
+- Reviewer for CVPR 2022, 2023
+- Reviewer for ICCV 2023
+- Reviewer for ECCV 2022
+- Reviewer for ICPR 2022
+- Reviewer for IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
+- Reviewer for Pattern Recognition (PR)
+
+# Awards & Honors
+
+2021 China National Scholarship