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Character Animation aims to generating character videos from still images through driving signals. Currently, diffusion models have become the mainstream in visual generation research, owing to their robust generative capabilities. However,…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Li Hu , Xin Gao , Peng Zhang , Ke Sun , Bang Zhang , Liefeng Bo

Diffusion and flow matching models have unlocked unprecedented capabilities for creative content creation, such as interactive image and streaming video generation. The growing demand for higher resolutions, frame rates, and context…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Brian Chao , Lior Yariv , Howard Xiao , Gordon Wetzstein

We present MOFA-Video, an advanced controllable image animation method that generates video from the given image using various additional controllable signals (such as human landmarks reference, manual trajectories, and another even…

Computer Vision and Pattern Recognition · Computer Science 2024-07-12 Muyao Niu , Xiaodong Cun , Xintao Wang , Yong Zhang , Ying Shan , Yinqiang Zheng

This work introduces Video Diffusion Transformer (VDT), which pioneers the use of transformers in diffusion-based video generation. It features transformer blocks with modularized temporal and spatial attention modules to leverage the rich…

Computer Vision and Pattern Recognition · Computer Science 2023-10-12 Haoyu Lu , Guoxing Yang , Nanyi Fei , Yuqi Huo , Zhiwu Lu , Ping Luo , Mingyu Ding

Human motion generation is a significant pursuit in generative computer vision with widespread applications in film-making, video games, AR/VR, and human-robot interaction. Current methods mainly utilize either diffusion-based generative…

Computer Vision and Pattern Recognition · Computer Science 2025-02-03 Canxuan Gang

Diffusion Transformer(DiT)-based generation models have achieved remarkable success in video generation. However, their inherent computational demands pose significant efficiency challenges. In this paper, we exploit the inherent temporal…

Computer Vision and Pattern Recognition · Computer Science 2025-04-17 Zhihang Yuan , Rui Xie , Yuzhang Shang , Hanling Zhang , Siyuan Wang , Shengen Yan , Guohao Dai , Yu Wang

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

Text-conditioned diffusion models have emerged as powerful tools for high-quality video generation. However, enabling Interactive Video Generation (IVG), where users control motion elements such as object trajectory, remains challenging.…

Computer Vision and Pattern Recognition · Computer Science 2025-06-02 Ishaan Rawal , Suryansh Kumar

With the advancement of generative artificial intelligence, previous studies have achieved the task of generating aesthetic images from hand-drawn sketches, fulfilling the public's needs for drawing. However, these methods are limited to…

Computer Vision and Pattern Recognition · Computer Science 2025-02-18 Lifan Jiang , Shuang Chen , Boxi Wu , Xiaotong Guan , Jiahui Zhang

Photo-realistic and controllable 3D avatars are crucial for various applications such as virtual and mixed reality (VR/MR), telepresence, gaming, and film production. Traditional methods for avatar creation often involve time-consuming…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Keqiang Sun , Amin Jourabloo , Riddhish Bhalodia , Moustafa Meshry , Yu Rong , Zhengyu Yang , Thu Nguyen-Phuoc , Christian Haene , Jiu Xu , Sam Johnson , Hongsheng Li , Sofien Bouaziz

Modern visual effects (VFX) software has made it possible for skilled artists to create imagery of virtually anything. However, the creation process remains laborious, complex, and largely inaccessible to everyday users. In this work, we…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 Hao-Yu Hsu , Zhi-Hao Lin , Albert Zhai , Hongchi Xia , Shenlong Wang

Text-driven image and video diffusion models have recently achieved unprecedented generation realism. While diffusion models have been successfully applied for image editing, very few works have done so for video editing. We present the…

Computer Vision and Pattern Recognition · Computer Science 2023-02-03 Eyal Molad , Eliahu Horwitz , Dani Valevski , Alex Rav Acha , Yossi Matias , Yael Pritch , Yaniv Leviathan , Yedid Hoshen

Over recent years, diffusion models have facilitated significant advancements in video generation. Yet, the creation of face-related videos still confronts issues such as low facial fidelity, lack of frame consistency, limited editability…

Computer Vision and Pattern Recognition · Computer Science 2023-12-22 Linze Li , Sunqi Fan , Hengjun Pu , Zhaodong Bing , Yao Tang , Tianzhu Ye , Tong Yang , Liangyu Chen , Jiajun Liang

Generating animated 3D objects is at the heart of many applications, yet most advanced works are typically difficult to apply in practice because of their limited setup, their long runtime, or their limited quality. We introduce ActionMesh,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-02 Remy Sabathier , David Novotny , Niloy J. Mitra , Tom Monnier

Recent advancements in video generation models have significantly improved their ability to follow text prompts. However, the customization of dynamic visual effects, defined as temporally evolving and appearance-driven visual phenomena…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Rui Zhao , Mike Zheng Shou

Long-range human movement generation remains a central challenge in computer vision and graphics. Generating coherent transitions across semantically distinct motion domains remains largely unexplored. This capability is particularly…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Haichao Wang , Alexander Okupnik , Yuxing Han , Gene Wen , Johannes Schneider , Kyriakos Flouris

The emergence of Diffusion Transformers (DiT) has brought significant advancements to video generation, especially in text-to-video and image-to-video tasks. Although video generation is widely applied in various fields, most existing…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Sen Liang , Zhentao Yu , Zhengguang Zhou , Teng Hu , Hongmei Wang , Yi Chen , Qin Lin , Yuan Zhou , Xin Li , Qinglin Lu , Zhibo Chen

Collaborative driving systems leverage vehicle-to-everything (V2X) communication for multi-agent collaborative perception to enhance driving safety, yet they remain constrained by scarce annotated real-world V2X driving datasets and limited…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Yihang Tao , Yu Guo , Senkang Hu , Yanan Ma , Zihan Fang , Sam Kwong , Yuguang Fang

Diffusion models have achieved remarkable progress in video generation, but their controllability remains a major limitation. Key scene factors such as layout, lighting, and camera trajectory are often entangled or only weakly modeled,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-10 Ziqi Cai , Taoyu Yang , Zheng Chang , Si Li , Han Jiang , Shuchen Weng , Boxin Shi

Transition videos play a crucial role in media production, enhancing the flow and coherence of visual narratives. Traditional methods like morphing often lack artistic appeal and require specialized skills, limiting their effectiveness.…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Rui Zhang , Yaosen Chen , Yuegen Liu , Wei Wang , Xuming Wen , Hongxia Wang