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A recent endeavor in one class of video anomaly detection is to leverage diffusion models and posit the task as a generation problem, where the diffusion model is trained to recover normal patterns exclusively, thus reporting abnormal…

Computer Vision and Pattern Recognition · Computer Science 2024-12-13 Hang Zhou , Jiale Cai , Yuteng Ye , Yonghui Feng , Chenxing Gao , Junqing Yu , Zikai Song , Wei Yang

Diffusion models have been central to the development of recent image, video, and even text generation systems. They posses striking geometric properties that can be faithfully portrayed in low-dimensional settings. However, existing…

Machine Learning · Computer Science 2025-07-08 Alec Helbling , Duen Horng Chau

Image stitching from different captures often results in non-rectangular boundaries, which is often considered unappealing. To solve non-rectangular boundaries, current solutions involve cropping, which discards image content, inpainting,…

Computer Vision and Pattern Recognition · Computer Science 2024-03-29 Tianhao Zhou , Haipeng Li , Ziyi Wang , Ao Luo , Chen-Lin Zhang , Jiajun Li , Bing Zeng , Shuaicheng Liu

Diffusion models have achieved significant success in image and video generation. This motivates a growing interest in video editing tasks, where videos are edited according to provided text descriptions. However, most existing approaches…

Computer Vision and Pattern Recognition · Computer Science 2023-12-01 Zhen Xing , Qi Dai , Zihao Zhang , Hui Zhang , Han Hu , Zuxuan Wu , Yu-Gang Jiang

Video-based human pose transfer is a video-to-video generation task that animates a plain source human image based on a series of target human poses. Considering the difficulties in transferring highly structural patterns on the garments…

Computer Vision and Pattern Recognition · Computer Science 2023-07-19 Wing-Yin Yu , Lai-Man Po , Ray C. C. Cheung , Yuzhi Zhao , Yu Xue , Kun Li

In this work, we rethink the approach to video super-resolution by introducing a method based on the Diffusion Posterior Sampling framework, combined with an unconditional video diffusion transformer operating in latent space. The video…

Computer Vision and Pattern Recognition · Computer Science 2025-11-05 Zhihao Zhan , Wang Pang , Xiang Zhu , Yechao Bai

Diffusion models have opened the path to a wide range of text-based image editing frameworks. However, these typically build on the multi-step nature of the diffusion backwards process, and adapting them to distilled, fast-sampling methods…

Computer Vision and Pattern Recognition · Computer Science 2024-08-02 Gilad Deutch , Rinon Gal , Daniel Garibi , Or Patashnik , Daniel Cohen-Or

Mixed reality applications require tracking the user's full-body motion to enable an immersive experience. However, typical head-mounted devices can only track head and hand movements, leading to a limited reconstruction of full-body motion…

Computer Vision and Pattern Recognition · Computer Science 2023-04-24 Angela Castillo , Maria Escobar , Guillaume Jeanneret , Albert Pumarola , Pablo Arbeláez , Ali Thabet , Artsiom Sanakoyeu

Generating coherent and diverse human dances from music signals has gained tremendous progress in animating virtual avatars. While existing methods support direct dance synthesis, they fail to recognize that enabling users to edit dance…

Graphics · Computer Science 2025-08-26 Hengyuan Zhang , Zhe Li , Xingqun Qi , Mengze Li , Muyi Sun , Man Zhang , Sirui Han

This paper proposes ConsistDreamer - a novel framework that lifts 2D diffusion models with 3D awareness and 3D consistency, thus enabling high-fidelity instruction-guided scene editing. To overcome the fundamental limitation of missing 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Jun-Kun Chen , Samuel Rota Bulò , Norman Müller , Lorenzo Porzi , Peter Kontschieder , Yu-Xiong Wang

The emergence of diffusion models has greatly propelled the progress in image and video generation. Recently, some efforts have been made in controllable video generation, including text-to-video generation and video motion control, among…

Computer Vision and Pattern Recognition · Computer Science 2024-05-02 Teng Hu , Jiangning Zhang , Ran Yi , Yating Wang , Hongrui Huang , Jieyu Weng , Yabiao Wang , Lizhuang Ma

Recent advances in generative AI have significantly enhanced image and video editing, particularly in the context of text prompt control. State-of-the-art approaches predominantly rely on diffusion models to accomplish these tasks. However,…

Computer Vision and Pattern Recognition · Computer Science 2024-04-03 Haoyu Ma , Shahin Mahdizadehaghdam , Bichen Wu , Zhipeng Fan , Yuchao Gu , Wenliang Zhao , Lior Shapira , Xiaohui Xie

Large-scale text-to-video models have shown remarkable abilities, but their direct application in video editing remains challenging due to limited available datasets. Current video editing methods commonly require per-video fine-tuning of…

Computer Vision and Pattern Recognition · Computer Science 2024-06-06 Zhenghao Zhang , Zuozhuo Dai , Long Qin , Weizhi Wang

Over the past few years, the automatic generation of facial animation for virtual characters has garnered interest among the animation research and industry communities. Recent research contributions leverage machine-learning approaches to…

Graphics · Computer Science 2020-07-21 Eloïse Berson , Catherine Soladié , Vincent Barrielle , Nicolas Stoiber

We are witnessing a revolution in conditional image synthesis with the recent success of large scale text-to-image generation methods. This success also opens up new opportunities in controlling the generation and editing process using…

Computer Vision and Pattern Recognition · Computer Science 2024-05-03 Burak Can Biner , Farrin Marouf Sofian , Umur Berkay Karakaş , Duygu Ceylan , Erkut Erdem , Aykut Erdem

The ability to manipulate objects in a desired configurations is a fundamental requirement for robots to complete various practical applications. While certain goals can be achieved by picking and placing the objects of interest directly,…

Robotics · Computer Science 2023-09-18 Utkarsh A. Mishra , Yongxin Chen

3D Human motion style transfer is a fundamental problem in computer graphic and animation processing. Existing AdaIN- based methods necessitate datasets with balanced style distribution and content/style labels to train the clustered latent…

Graphics · Computer Science 2024-08-08 Lei Hu , Zihao Zhang , Yongjing Ye , Yiwen Xu , Shihong Xia

Existing text-driven 3D human motion editing methods have demonstrated significant progress, but are still difficult to precisely control over detailed, part-specific motions due to their global modeling nature. In this paper, we propose…

Graphics · Computer Science 2026-01-01 Yujie Yang , Zhichao Zhang , Jiazhou Chen , Zichao Wu

Accurate and controllable image editing is a challenging task that has attracted significant attention recently. Notably, DragGAN is an interactive point-based image editing framework that achieves impressive editing results with…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Yujun Shi , Chuhui Xue , Jun Hao Liew , Jiachun Pan , Hanshu Yan , Wenqing Zhang , Vincent Y. F. Tan , Song Bai

Diffusion models have made significant advances in text-guided synthesis tasks. However, editing user-provided images remains challenging, as the high dimensional noise input space of diffusion models is not naturally suited for image…

Computer Vision and Pattern Recognition · Computer Science 2024-04-25 Jiteng Mu , Michaël Gharbi , Richard Zhang , Eli Shechtman , Nuno Vasconcelos , Xiaolong Wang , Taesung Park