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Video generation has recently emerged as a central task in the field of generative AI. However, the substantial computational cost inherent in video synthesis makes model distillation a critical technique for efficient deployment. Despite…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Yuyang You , Yongzhi Li , Jiahui Li , Yadong Mu , Quan Chen , Peng Jiang

Image tiling -- the seamless connection of disparate images to create a coherent visual field -- is crucial for applications such as texture creation, video game asset development, and digital art. Traditionally, tiles have been constructed…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Or Madar , Ohad Fried

Generating temporally coherent high fidelity video is an important milestone in generative modeling research. We make progress towards this milestone by proposing a diffusion model for video generation that shows very promising initial…

Computer Vision and Pattern Recognition · Computer Science 2022-06-24 Jonathan Ho , Tim Salimans , Alexey Gritsenko , William Chan , Mohammad Norouzi , David J. Fleet

Video try-on stands as a promising area for its tremendous real-world potential. Previous research on video try-on has primarily focused on transferring product clothing images to videos with simple human poses, while performing poorly with…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Jun Zheng , Jing Wang , Fuwei Zhao , Xujie Zhang , Xiaodan Liang

Research on video generation has recently made tremendous progress, enabling high-quality videos to be generated from text prompts or images. Adding control to the video generation process is an important goal moving forward and recent…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Zhengfei Kuang , Shengqu Cai , Hao He , Yinghao Xu , Hongsheng Li , Leonidas Guibas , Gordon Wetzstein

High-fidelity video generation remains challenging for diffusion models due to the difficulty of modeling complex spatio-temporal dynamics efficiently. Recent video diffusion methods typically represent a video as a sequence of…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Minh Khoa Le , Kien Do , Duc Thanh Nguyen , Truyen Tran

Despite recent advances in diffusion transformers (DiTs) for text-to-video generation, scaling to long-duration content remains challenging due to the quadratic complexity of self-attention. While prior efforts -- such as sparse attention…

Computer Vision and Pattern Recognition · Computer Science 2025-07-18 Jiaxiu Jiang , Wenbo Li , Jingjing Ren , Yuping Qiu , Yong Guo , Xiaogang Xu , Han Wu , Wangmeng Zuo

While Diffusion Transformers (DiTs) have achieved notable progress in video generation, this long-sequence generation task remains constrained by the quadratic complexity inherent to self-attention mechanisms, creating significant barriers…

Computer Vision and Pattern Recognition · Computer Science 2026-02-04 Yuxi Liu , Yipeng Hu , Zekun Zhang , Kunze Jiang , Kun Yuan

Interactive image editing allows users to modify images through visual interaction operations such as drawing, clicking, and dragging. Existing methods construct such supervision signals from videos, as they capture how objects change with…

Computer Vision and Pattern Recognition · Computer Science 2025-01-15 Yabo Zhang , Xinpeng Zhou , Yihan Zeng , Hang Xu , Hui Li , Wangmeng Zuo

Generating high-quality and person-generic visual dubbing remains a challenge. Recent innovation has seen the advent of a two-stage paradigm, decoupling the rendering and lip synchronization process facilitated by intermediate…

Computer Vision and Pattern Recognition · Computer Science 2024-01-15 Tao Liu , Chenpeng Du , Shuai Fan , Feilong Chen , Kai Yu

Fine-grained and efficient controllability on video diffusion transformers has raised increasing desires for the applicability. Recently, In-context Conditioning emerged as a powerful paradigm for unified conditional video generation, which…

Computer Vision and Pattern Recognition · Computer Science 2025-06-06 Xuanhua He , Quande Liu , Zixuan Ye , Weicai Ye , Qiulin Wang , Xintao Wang , Qifeng Chen , Pengfei Wan , Di Zhang , Kun Gai

Generating high-dimensional visual modalities is a computationally intensive task. A common solution is progressive generation, where the outputs are synthesized in a coarse-to-fine spectral autoregressive manner. While diffusion models…

Computer Vision and Pattern Recognition · Computer Science 2025-06-25 Moayed Haji-Ali , Willi Menapace , Ivan Skorokhodov , Arpit Sahni , Sergey Tulyakov , Vicente Ordonez , Aliaksandr Siarohin

Synthesizing consistent and photorealistic 3D scenes is an open problem in computer vision. Video diffusion models generate impressive videos but cannot directly synthesize 3D representations, i.e., lack 3D consistency in the generated…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Katja Schwarz , Norman Mueller , Peter Kontschieder

Diffusion Transformer (DiT)-based video diffusion models generate high-quality videos at scale but incur prohibitive processing latency and memory costs for long videos. To address this, we propose a novel distributed inference strategy,…

Computer Vision and Pattern Recognition · Computer Science 2025-05-30 Zeqing Wang , Bowen Zheng , Xingyi Yang , Zhenxiong Tan , Yuecong Xu , Xinchao Wang

Effective trajectory stitching for long-horizon planning is a significant challenge in robotic decision-making. While diffusion models have shown promise in planning, they are limited to solving tasks similar to those seen in their training…

Robotics · Computer Science 2025-05-06 Yunhao Luo , Utkarsh A. Mishra , Yilun Du , Danfei Xu

When editing a video, a piece of attractive background music is indispensable. However, video background music generation tasks face several challenges, for example, the lack of suitable training datasets, and the difficulties in flexibly…

Computer Vision and Pattern Recognition · Computer Science 2024-05-21 Sizhe Li , Yiming Qin , Minghang Zheng , Xin Jin , Yang Liu

Identity-preserving text-to-video (IPT2V) generation aims to create high-fidelity videos with consistent human identity. It is an important task in video generation but remains an open problem for generative models. This paper pushes the…

Computer Vision and Pattern Recognition · Computer Science 2025-03-27 Shenghai Yuan , Jinfa Huang , Xianyi He , Yunyuan Ge , Yujun Shi , Liuhan Chen , Jiebo Luo , Li Yuan

By generating plausible and smooth transitions between two image frames, video inbetweening is an essential tool for video editing and long video synthesis. Traditional works lack the capability to generate complex large motions. While…

Computer Vision and Pattern Recognition · Computer Science 2025-01-09 Maham Tanveer , Yang Zhou , Simon Niklaus , Ali Mahdavi Amiri , Hao Zhang , Krishna Kumar Singh , Nanxuan Zhao

Safe trajectory planning in complex environments must balance stringent collision avoidance with real-time efficiency, which is a long-standing challenge in robotics. In this work, we present a diffusion-based trajectory planning framework…

Robotics · Computer Science 2025-11-27 Wule Mao , Zhouheng Li , Yunhao Luo , Yilun Du , Lei Xie

Recent text-to-image generative models can generate high-fidelity images from text prompts. However, these models struggle to consistently generate the same objects in different contexts with the same appearance. Consistent object…

Computer Vision and Pattern Recognition · Computer Science 2023-10-12 Alec Helbling , Evan Montoya , Duen Horng Chau
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