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README.md

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 license: openrail
 ---
 
-# This repo contains the pretrained checkpoints for Ctrl-Adapter
+# This repo contains the VPLM Dataset and pretrained checkpoints for RACCooN
 
 
-CTRL-Adapter is an efficient and versatile framework for adding diverse
-spatial controls to any image or video diffusion model. It supports a variety of useful
-applications, including video control, video control with multiple conditions, video control with
-sparse frame conditions, image control, zero-shot transfer to unseen conditions, and video editing.
-
 See also: https://github.com/jaehong31/RACCooN
 
-
-<!-- <br>
+<br>
 <img width="800" src="assets/raccoon_teaser.png"/>
-<br> -->
+<br>
+<br>
+
+RACCooN is a versatile and user-friendly video-to-paragraph-to-video generative framework 
+that supports multiple video editing capabilities such as removal, addition, and modification, 
+through a unified pipeline. RACCooN consists of two principal stages: 
+Video-to-Paragraph (V2P) and Paragraph-to-Video (P2V).
+
+RACCooN suggests a multi-granular spatiotemporal pooling strategy to generate well-structured video descriptions, capturing both the broad context and object details without requiring complex human annotations, simplifying precise video content editing based on text for users. Our video generative model incorporates auto-generated narratives or instructions to enhance the quality and accuracy of the generated content. It supports the addition of video objects, inpainting, and attribute modification within a unified framework, surpassing existing video editing and inpainting benchmarks. 
+
+<br>
+<img width="800" src="assets/raccoon_method.png"/>
+<br>
 
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