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Conditional generative models typically demand large annotated training sets to achieve high-quality synthesis. As a result, there has been significant interest in designing models that perform plug-and-play generation, i.e., to use a…

Computer Vision and Pattern Recognition · Computer Science 2023-10-03 Nithin Gopalakrishnan Nair , Anoop Cherian , Suhas Lohit , Ye Wang , Toshiaki Koike-Akino , Vishal M. Patel , Tim K. Marks

Precise camera control for reshooting dynamic videos is bottlenecked by the severe scarcity of paired multi-view data for non-rigid scenes. We overcome this limitation with a highly scalable self-supervised framework capable of leveraging…

Computer Vision and Pattern Recognition · Computer Science 2026-04-27 Avinash Paliwal , Adithya Iyer , Shivin Yadav , Muhammad Ali Afridi , Midhun Harikumar

Generating long, high-quality videos remains a challenge due to the complex interplay of spatial and temporal dynamics and hardware limitations. In this work, we introduce MaskFlow, a unified video generation framework that combines…

Computer Vision and Pattern Recognition · Computer Science 2025-03-13 Michael Fuest , Vincent Tao Hu , Björn Ommer

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

The art of communication beyond speech there are gestures. The automatic co-speech gesture generation draws much attention in computer animation. It is a challenging task due to the diversity of gestures and the difficulty of matching the…

Human-Computer Interaction · Computer Science 2023-05-09 Sicheng Yang , Zhiyong Wu , Minglei Li , Zhensong Zhang , Lei Hao , Weihong Bao , Ming Cheng , Long Xiao

Although powerful for image generation, consistent and controllable video is a longstanding problem for diffusion models. Video models require extensive training and computational resources, leading to high costs and large environmental…

Computer Vision and Pattern Recognition · Computer Science 2024-10-10 Muhammad Haaris Khan , Hadrien Reynaud , Bernhard Kainz

Despite the rapid advancements in video generation technology, creating high-quality videos that precisely align with user intentions remains a significant challenge. Existing methods often fail to achieve fine-grained control over video…

Computer Vision and Pattern Recognition · Computer Science 2025-09-10 Wenshuo Gao , Xicheng Lan , Shuai Yang

One-shot talking head video generation uses a source image and driving video to create a synthetic video where the source person's facial movements imitate those of the driving video. However, differences in scale between the source and…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Fa-Ting Hong , Dan Xu

Current video generation models excel at short clips but fail to produce cohesive multi-shot narratives due to disjointed visual dynamics and fractured storylines. Existing solutions either rely on extensive manual scripting/editing or…

Computer Vision and Pattern Recognition · Computer Science 2025-10-03 Mingzhe Zheng , Yongqi Xu , Haojian Huang , Xuran Ma , Yexin Liu , Wenjie Shu , Yatian Pang , Feilong Tang , Qifeng Chen , Harry Yang , Ser-Nam Lim

Recent diffusion-based Single-image 3D portrait generation methods typically employ 2D diffusion models to provide multi-view knowledge, which is then distilled into 3D representations. However, these methods usually struggle to produce…

Computer Vision and Pattern Recognition · Computer Science 2024-11-18 Haoran Wei , Wencheng Han , Xingping Dong , Jianbing Shen

Generative AI has significantly changed industries by enabling text-driven image generation, yet challenges remain in achieving high-resolution outputs that align with fine-grained user preferences. Consequently, multi-round interactions…

Computer Vision and Pattern Recognition · Computer Science 2025-04-28 Kun Li , Jianhui Wang , Yangfan He , Xinyuan Song , Ruoyu Wang , Hongyang He , Wenxin Zhang , Jiaqi Chen , Keqin Li , Sida Li , Miao Zhang , Tianyu Shi , Xueqian Wang

While substantial progresses have been made in automated 2D portrait stylization, admirable 3D portrait stylization from a single user photo remains to be an unresolved challenge. One primary obstacle here is the lack of high quality…

Computer Vision and Pattern Recognition · Computer Science 2023-03-28 Guoxian Song , Hongyi Xu , Jing Liu , Tiancheng Zhi , Yichun Shi , Jianfeng Zhang , Zihang Jiang , Jiashi Feng , Shen Sang , Linjie Luo

Recent advances in AI-generated content (AIGC) have significantly accelerated animation production. To produce engaging animations, it is essential to generate coherent multi-shot video clips with narrative scripts and character references.…

Computer Vision and Pattern Recognition · Computer Science 2025-06-04 Lu Qiu , Yizhuo Li , Yuying Ge , Yixiao Ge , Ying Shan , Xihui Liu

Diffusion models have recently been employed to generate high-quality images, reducing the need for manual data collection and improving model generalization in tasks such as object detection, instance segmentation, and image perception.…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 You Li , Fan Ma , Yi Yang

Efficiently generating a freestyle 3D portrait with high quality and 3D-consistency is a promising yet challenging task. The portrait styles generated by most existing methods are usually restricted by their 3D generators, which are learned…

Computer Vision and Pattern Recognition · Computer Science 2023-12-27 Tianxiang Ma , Kang Zhao , Jianxin Sun , Yingya Zhang , Jing Dong

Recently, large-scale diffusion models, e.g., Stable diffusion and DallE2, have shown remarkable results on image synthesis. On the other hand, large-scale cross-modal pre-trained models (e.g., CLIP, ALIGN, and FILIP) are competent for…

Computer Vision and Pattern Recognition · Computer Science 2023-08-21 Runhui Huang , Jianhua Han , Guansong Lu , Xiaodan Liang , Yihan Zeng , Wei Zhang , Hang Xu

We propose DiffSHEG, a Diffusion-based approach for Speech-driven Holistic 3D Expression and Gesture generation with arbitrary length. While previous works focused on co-speech gesture or expression generation individually, the joint…

Sound · Computer Science 2024-04-09 Junming Chen , Yunfei Liu , Jianan Wang , Ailing Zeng , Yu Li , Qifeng Chen

Echocardiography (ECHO) is essential for cardiac assessments, but its video quality and interpretation heavily relies on manual expertise, leading to inconsistent results from clinical and portable devices. ECHO video generation offers a…

Image and Video Processing · Electrical Eng. & Systems 2024-10-15 Yiwei Li , Sekeun Kim , Zihao Wu , Hanqi Jiang , Yi Pan , Pengfei Jin , Sifan Song , Yucheng Shi , Tianming Liu , Quanzheng Li , Xiang Li

Training generative models, such as GANs, on a target domain containing limited examples (e.g., 10) can easily result in overfitting. In this work, we seek to utilize a large source domain for pretraining and transfer the diversity…

Computer Vision and Pattern Recognition · Computer Science 2021-04-15 Utkarsh Ojha , Yijun Li , Jingwan Lu , Alexei A. Efros , Yong Jae Lee , Eli Shechtman , Richard Zhang

Recent diffusion-based talking face generation models have demonstrated impressive potential in synthesizing videos that accurately match a speech audio clip with a given reference identity. However, existing approaches still encounter…

Computer Vision and Pattern Recognition · Computer Science 2025-10-16 Xingpei Ma , Jiaran Cai , Yuansheng Guan , Shenneng Huang , Qiang Zhang , Shunsi Zhang