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Recent advances in video diffusion models have unlocked new potential for realistic audio-driven talking video generation. However, achieving seamless audio-lip synchronization, maintaining long-term identity consistency, and producing…

Computer Vision and Pattern Recognition · Computer Science 2024-12-06 Longtao Zheng , Yifan Zhang , Hanzhong Guo , Jiachun Pan , Zhenxiong Tan , Jiahao Lu , Chuanxin Tang , Bo An , Shuicheng Yan

Diffusion-based models have gained wide adoption in the virtual human generation due to their outstanding expressiveness. However, their substantial computational requirements have constrained their deployment in real-time interactive…

Computer Vision and Pattern Recognition · Computer Science 2025-06-09 Haojie Yu , Zhaonian Wang , Yihan Pan , Meng Cheng , Hao Yang , Chao Wang , Tao Xie , Xiaoming Xu , Xiaoming Wei , Xunliang Cai

The spatio-temporal complexity of video data presents significant challenges in tasks such as compression, generation, and inpainting. We present four key contributions to address the challenges of spatiotemporal video processing. First, we…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Onkar Susladkar , Jishu Sen Gupta , Chirag Sehgal , Sparsh Mittal , Rekha Singhal

Portrait animation aims to generate photo-realistic videos from a single source image by reenacting the expression and pose from a driving video. While early methods relied on 3D morphable models or feature warping techniques, they often…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Mallikarjun B. R. , Fei Yin , Vikram Voleti , Nikita Drobyshev , Maksim Lapin , Aaryaman Vasishta , Varun Jampani

Medical video generation models are expected to have a profound impact on the healthcare industry, including but not limited to medical education and training, surgical planning, and simulation. Current video diffusion models typically…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 Zhenbin Wang , Lei Zhang , Lituan Wang , Minjuan Zhu , Zhenwei Zhang

Recent advances in diffusion models bring new vitality to visual content creation. However, current text-to-video generation models still face significant challenges such as high training costs, substantial data requirements, and…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Sicong Feng , Jielong Yang , Li Peng

Recent years have seen substantial progress in diffusion-based controllable video generation. However, achieving precise control in complex scenarios, including fine-grained object parts, sophisticated motion trajectories, and coherent…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Haitao Zhou , Chuang Wang , Rui Nie , Jinlin Liu , Dongdong Yu , Qian Yu , Changhu Wang

Video generation has achieved remarkable progress with the introduction of diffusion models, which have significantly improved the quality of generated videos. However, recent research has primarily focused on scaling up model training,…

Computer Vision and Pattern Recognition · Computer Science 2025-01-16 Chenyang Si , Weichen Fan , Zhengyao Lv , Ziqi Huang , Yu Qiao , Ziwei Liu

Traditional 3D content creation tools empower users to bring their imagination to life by giving them direct control over a scene's geometry, appearance, motion, and camera path. Creating computer-generated videos, however, is a tedious…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Shengqu Cai , Duygu Ceylan , Matheus Gadelha , Chun-Hao Paul Huang , Tuanfeng Yang Wang , Gordon Wetzstein

We present On-device Sora, the first model training-free solution for diffusion-based on-device text-to-video generation that operates efficiently on smartphone-grade devices. To address the challenges of diffusion-based text-to-video…

Computer Vision and Pattern Recognition · Computer Science 2025-04-02 Bosung Kim , Kyuhwan Lee , Isu Jeong , Jungmin Cheon , Yeojin Lee , Seulki Lee

We present On-device Sora, the first model training-free solution for diffusion-based on-device text-to-video generation that operates efficiently on smartphone-grade devices. To address the challenges of diffusion-based text-to-video…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Bosung Kim , Kyuhwan Lee , Isu Jeong , Jungmin Cheon , Yeojin Lee , Seulki Lee

Talking head generation with arbitrary identities and speech audio remains a crucial problem in the realm of the virtual metaverse. Recently, diffusion models have become a popular generative technique in this field with their strong…

Graphics · Computer Science 2025-08-11 Xinyang Li , Gen Li , Zhihui Lin , Yichen Qian , GongXin Yao , Weinan Jia , Aowen Wang , Weihua Chen , Fan Wang

The recent wave of AI-generated content (AIGC) has witnessed substantial success in computer vision, with the diffusion model playing a crucial role in this achievement. Due to their impressive generative capabilities, diffusion models are…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Zhen Xing , Qijun Feng , Haoran Chen , Qi Dai , Han Hu , Hang Xu , Zuxuan Wu , Yu-Gang Jiang

Recently, diffusion-based video generation models have achieved significant success. However, existing models often suffer from issues like weak consistency and declining image quality over time. To overcome these challenges, inspired by…

Computer Vision and Pattern Recognition · Computer Science 2024-12-13 Delong Liu , Zhaohui Hou , Mingjie Zhan , Shihao Han , Zhicheng Zhao , Fei Su

Recent video inpainting algorithms integrate flow-based pixel propagation with transformer-based generation to leverage optical flow for restoring textures and objects using information from neighboring frames, while completing masked…

Computer Vision and Pattern Recognition · Computer Science 2025-01-20 Xiaowen Li , Haolan Xue , Peiran Ren , 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

Talking face generation has historically struggled to produce head movements and natural facial expressions without guidance from additional reference videos. Recent developments in diffusion-based generative models allow for more realistic…

Computer Vision and Pattern Recognition · Computer Science 2023-08-01 Michał Stypułkowski , Konstantinos Vougioukas , Sen He , Maciej Zięba , Stavros Petridis , Maja Pantic

The impressive achievements of generative models in creating high-quality videos have raised concerns about digital integrity and privacy vulnerabilities. Recent works to combat Deepfakes videos have developed detectors that are highly…

Computer Vision and Pattern Recognition · Computer Science 2024-06-17 Qingyuan Liu , Pengyuan Shi , Yun-Yun Tsai , Chengzhi Mao , Junfeng Yang

A key challenge with procedure planning in instructional videos lies in how to handle a large decision space consisting of a multitude of action types that belong to various tasks. To understand real-world video content, an AI agent must…

Computer Vision and Pattern Recognition · Computer Science 2023-09-15 Fen Fang , Yun Liu , Ali Koksal , Qianli Xu , Joo-Hwee Lim

Instructional video generation is an emerging task that aims to synthesize coherent demonstrations of procedural activities from textual descriptions. Such capability has broad implications for content creation, education, and human-AI…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Cheeun Hong , German Barquero , Fadime Sener , Markos Georgopoulos , Edgar Schönfeld , Stefan Popov , Yuming Du , Oscar Mañas , Albert Pumarola
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