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Diffusion models have achieved remarkable success in generating high quality image and video data. More recently, they have also been used for image compression with high perceptual quality. In this paper, we present a novel approach to…

Image and Video Processing · Electrical Eng. & Systems 2024-02-15 Bohan Li , Yiming Liu , Xueyan Niu , Bo Bai , Lei Deng , Deniz Gündüz

Tracking a point through a video can be a challenging task due to uncertainty arising from visual obfuscations, such as appearance changes and occlusions. Although current state-of-the-art discriminative models excel in regressing long-term…

Computer Vision and Pattern Recognition · Computer Science 2025-10-27 Mattie Tesfaldet , Adam W. Harley , Konstantinos G. Derpanis , Derek Nowrouzezahrai , Christopher Pal

Customized generation using diffusion models has made impressive progress in image generation, but remains unsatisfactory in the challenging video generation task, as it requires the controllability of both subjects and motions. To that…

Computer Vision and Pattern Recognition · Computer Science 2023-12-08 Yujie Wei , Shiwei Zhang , Zhiwu Qing , Hangjie Yuan , Zhiheng Liu , Yu Liu , Yingya Zhang , Jingren Zhou , Hongming Shan

In professional video compositing workflows, artists must manually create environmental interactions-such as shadows, reflections, dust, and splashes-between foreground subjects and background layers. Existing video generative models…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Luchao Qi , Jiaye Wu , Jun Myeong Choi , Cary Phillips , Roni Sengupta , Dan B Goldman

The pursuit of controllability as a higher standard of visual content creation has yielded remarkable progress in customizable image synthesis. However, achieving controllable video synthesis remains challenging due to the large variation…

Computer Vision and Pattern Recognition · Computer Science 2023-06-07 Xiang Wang , Hangjie Yuan , Shiwei Zhang , Dayou Chen , Jiuniu Wang , Yingya Zhang , Yujun Shen , Deli Zhao , Jingren Zhou

This paper addresses the challenge of text-conditioned streaming motion generation, which requires us to predict the next-step human pose based on variable-length historical motions and incoming texts. Existing methods struggle to achieve…

Computer Vision and Pattern Recognition · Computer Science 2025-08-08 Lixing Xiao , Shunlin Lu , Huaijin Pi , Ke Fan , Liang Pan , Yueer Zhou , Ziyong Feng , Xiaowei Zhou , Sida Peng , Jingbo Wang

Recent advancements in video diffusion models based on Diffusion Transformers (DiTs) have achieved remarkable success in generating temporally coherent videos. Yet, a fundamental question persists: how do these models internally establish…

Computer Vision and Pattern Recognition · Computer Science 2025-06-24 Jisu Nam , Soowon Son , Dahyun Chung , Jiyoung Kim , Siyoon Jin , Junhwa Hur , Seungryong Kim

Video outpainting is a challenging task that generates new video content by extending beyond the boundaries of an original input video, requiring both temporal and spatial consistency. Many state-of-the-art methods utilize latent diffusion…

Computer Vision and Pattern Recognition · Computer Science 2025-06-30 Linhao Zhong , Fan Li , Yi Huang , Jianzhuang Liu , Renjing Pei , Fenglong Song

Diffusion Transformers (DiT) have shown strong performance in video generation tasks, but their high computational cost makes them impractical for resource-constrained devices like smartphones, and practical on-device generation is even…

Computer Vision and Pattern Recognition · Computer Science 2025-10-01 Yushu Wu , Yanyu Li , Anil Kag , Ivan Skorokhodov , Willi Menapace , Ke Ma , Arpit Sahni , Ju Hu , Aliaksandr Siarohin , Dhritiman Sagar , Yanzhi Wang , Sergey Tulyakov

Generating high-quality 360{\deg} panoramic videos from perspective input is one of the crucial applications for virtual reality (VR), whereby high-resolution videos are especially important for immersive experience. Existing methods are…

Computer Vision and Pattern Recognition · Computer Science 2026-03-05 Lingen Li , Guangzhi Wang , Xiaoyu Li , Zhaoyang Zhang , Qi Dou , Jinwei Gu , Tianfan Xue , Ying Shan

Recent advances in video generation models has significantly accelerated video generation and related downstream tasks. Among these, video stylization holds important research value in areas such as immersive applications and artistic…

Computer Vision and Pattern Recognition · Computer Science 2026-04-16 Hengye Lyu , Zisu Li , Yue Hong , Yueting Weng , Jiaxin Shi , Hanwang Zhang , Chen Liang

Large-scale Text-to-Video (T2V) diffusion models have recently demonstrated unprecedented capability to transform natural language descriptions into stunning and photorealistic videos. Despite the promising results, a significant challenge…

Computer Vision and Pattern Recognition · Computer Science 2024-07-09 Xingyi Yang , Xinchao Wang

Compositing an object into an image involves multiple non-trivial sub-tasks such as object placement and scaling, color/lighting harmonization, viewpoint/geometry adjustment, and shadow/reflection generation. Recent generative image…

Computer Vision and Pattern Recognition · Computer Science 2024-09-12 Gemma Canet Tarrés , Zhe Lin , Zhifei Zhang , Jianming Zhang , Yizhi Song , Dan Ruta , Andrew Gilbert , John Collomosse , Soo Ye Kim

While text-to-video diffusion models have made significant strides, many still face challenges in generating videos with temporal consistency. Within diffusion frameworks, guidance techniques have proven effective in enhancing output…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Hyelin Nam , Jaemin Kim , Dohun Lee , Jong Chul Ye

Recent advances in diffusion models have demonstrated remarkable capabilities in video generation. However, the computational intensity remains a significant challenge for practical applications. While feature caching has been proposed to…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Xuran Ma , Yexin Liu , Yaofu Liu , Xianfeng Wu , Mingzhe Zheng , Zihao Wang , Ser-Nam Lim , Harry Yang

Creating a vivid video from the event or scenario in our imagination is a truly fascinating experience. Recent advancements in text-to-video synthesis have unveiled the potential to achieve this with prompts only. While text is convenient…

Computer Vision and Pattern Recognition · Computer Science 2023-06-02 Jinbo Xing , Menghan Xia , Yuxin Liu , Yuechen Zhang , Yong Zhang , Yingqing He , Hanyuan Liu , Haoxin Chen , Xiaodong Cun , Xintao Wang , Ying Shan , Tien-Tsin Wong

Text-driven video generation witnesses rapid progress. However, merely using text prompts is not enough to depict the desired subject appearance that accurately aligns with users' intents, especially for customized content creation. In this…

Computer Vision and Pattern Recognition · Computer Science 2023-12-04 Yuming Jiang , Tianxing Wu , Shuai Yang , Chenyang Si , Dahua Lin , Yu Qiao , Chen Change Loy , Ziwei Liu

Text-driven content creation has evolved to be a transformative technique that revolutionizes creativity. Here we study the task of text-driven human video generation, where a video sequence is synthesized from texts describing the…

Computer Vision and Pattern Recognition · Computer Science 2023-04-18 Yuming Jiang , Shuai Yang , Tong Liang Koh , Wayne Wu , Chen Change Loy , Ziwei Liu

With the advance of diffusion models, today's video generation has achieved impressive quality. But generating temporal consistent long videos is still challenging. A majority of video diffusion models (VDMs) generate long videos in an…

Computer Vision and Pattern Recognition · Computer Science 2024-06-18 Kaifeng Gao , Jiaxin Shi , Hanwang Zhang , Chunping Wang , Jun Xiao

We present DriveGen3D, a novel framework for generating high-quality and highly controllable dynamic 3D driving scenes that addresses critical limitations in existing methodologies. Current approaches to driving scene synthesis either…