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Denoising diffusion models have shown great promise in human motion synthesis conditioned on natural language descriptions. However, integrating spatial constraints, such as pre-defined motion trajectories and obstacles, remains a challenge…

Computer Vision and Pattern Recognition · Computer Science 2023-10-31 Korrawe Karunratanakul , Konpat Preechakul , Supasorn Suwajanakorn , Siyu Tang

Video generation has drawn significant interest recently, pushing the development of large-scale models capable of producing realistic videos with coherent motion. Due to memory constraints, these models typically generate short video…

Computer Vision and Pattern Recognition · Computer Science 2024-07-23 Idan Kligvasser , Regev Cohen , George Leifman , Ehud Rivlin , Michael Elad

In layout-to-image (L2I) synthesis, controlled complex scenes are generated from coarse information like bounding boxes. Such a task is exciting to many downstream applications because the input layouts offer strong guidance to the…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Ruyu Wang , Xuefeng Hou , Sabrina Schmedding , Marco F. Huber

Focus is a cornerstone of photography, yet autofocus systems often fail to capture the intended subject, and users frequently wish to adjust focus after capture. We introduce a novel method for realistic post-capture refocusing using video…

Computer Vision and Pattern Recognition · Computer Science 2025-12-30 SaiKiran Tedla , Zhoutong Zhang , Xuaner Zhang , Shumian Xin

Diffusion Policy (DP) enables robots to learn complex behaviors by imitating expert demonstrations through action diffusion. However, in practical applications, hardware limitations often degrade data quality, while real-time constraints…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Jiahua Ma , Yiran Qin , Yixiong Li , Xuanqi Liao , Yulan Guo , Ruimao Zhang

Recent advances in motion diffusion models have led to remarkable progress in diverse motion generation tasks, including text-to-motion synthesis. However, existing approaches represent motions as dense frame sequences, requiring the model…

Computer Vision and Pattern Recognition · Computer Science 2025-05-13 Jinseok Bae , Inwoo Hwang , Young Yoon Lee , Ziyu Guo , Joseph Liu , Yizhak Ben-Shabat , Young Min Kim , Mubbasir Kapadia

Image generation and editing have seen a great deal of advancements with the rise of large-scale diffusion models that allow user control of different modalities such as text, mask, depth maps, etc. However, controlled editing of videos…

Computer Vision and Pattern Recognition · Computer Science 2024-06-04 AmirHossein Zamani , Amir G. Aghdam , Tiberiu Popa , Eugene Belilovsky

This paper presents a method that allows users to design cinematic video shots in the context of image-to-video generation. Shot design, a critical aspect of filmmaking, involves meticulously planning both camera movements and object…

Computer Vision and Pattern Recognition · Computer Science 2025-02-07 Jinbo Xing , Long Mai , Cusuh Ham , Jiahui Huang , Aniruddha Mahapatra , Chi-Wing Fu , Tien-Tsin Wong , Feng Liu

Large-scale text-to-video diffusion models have demonstrated an exceptional ability to synthesize diverse videos. However, due to the lack of extensive text-to-video datasets and the necessary computational resources for training, directly…

Computer Vision and Pattern Recognition · Computer Science 2023-05-10 Nisha Huang , Yuxin Zhang , Weiming Dong

Diffusion-based methods have achieved prominent success in generating 2D media. However, accomplishing similar proficiencies for scene-level mesh texturing in 3D spatial applications, e.g., XR/VR, remains constrained, primarily due to the…

Computer Vision and Pattern Recognition · Computer Science 2023-10-23 Bangbang Yang , Wenqi Dong , Lin Ma , Wenbo Hu , Xiao Liu , Zhaopeng Cui , Yuewen Ma

Human motion modeling is important for many modern graphics applications, which typically require professional skills. In order to remove the skill barriers for laymen, recent motion generation methods can directly generate human motions…

Computer Vision and Pattern Recognition · Computer Science 2022-09-01 Mingyuan Zhang , Zhongang Cai , Liang Pan , Fangzhou Hong , Xinying Guo , Lei Yang , Ziwei Liu

Text-guided video-to-video stylization transforms the visual appearance of a source video to a different appearance guided on textual prompts. Existing text-guided image diffusion models can be extended for stylized video synthesis.…

Computer Vision and Pattern Recognition · Computer Science 2023-11-27 Minshan Xie , Hanyuan Liu , Chengze Li , Tien-Tsin Wong

This paper addresses the problem of generating dynamically admissible trajectories for control tasks using diffusion models, particularly in scenarios where the environment is complex and system dynamics are crucial for practical…

Robotics · Computer Science 2025-10-15 Darshan Gadginmath , Fabio Pasqualetti

Unsupervised visual object tracking is a challenging task that requires following arbitrary targets in videos without training on ground-truth annotations. Despite considerable progress, existing state-of-the-art unsupervised trackers often…

Computer Vision and Pattern Recognition · Computer Science 2026-05-27 Zhengbo Zhang , Zhigang Tu , Junsong Yuan , De Wen Soh , Bo Du

Image synthesis is expected to provide value for the translation of machine learning methods into clinical practice. Fundamental problems like model robustness, domain transfer, causal modelling, and operator training become approachable…

Computer Vision and Pattern Recognition · Computer Science 2024-02-22 Hadrien Reynaud , Mengyun Qiao , Mischa Dombrowski , Thomas Day , Reza Razavi , Alberto Gomez , Paul Leeson , Bernhard Kainz

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

Text-to-image diffusion models pre-trained on billions of image-text pairs have recently enabled 3D content creation by optimizing a randomly initialized differentiable 3D representation with score distillation. However, the optimization…

Computer Vision and Pattern Recognition · Computer Science 2024-05-07 Yukun Huang , Jianan Wang , Yukai Shi , Boshi Tang , Xianbiao Qi , Lei Zhang

Recent advancements have integrated camera pose as a user-friendly and physics-informed condition in video diffusion models, enabling precise camera control. In this paper, we identify one of the key challenges as effectively modeling noisy…

Computer Vision and Pattern Recognition · Computer Science 2024-12-05 Guangcong Zheng , Teng Li , Rui Jiang , Yehao Lu , Tao Wu , Xi Li

Recently, the multimedia community has witnessed the rise of diffusion models trained on large-scale multi-modal data for visual content creation, particularly in the field of text-to-image generation. In this paper, we propose a new task…

Computer Vision and Pattern Recognition · Computer Science 2023-11-10 Jingwen Chen , Yingwei Pan , Ting Yao , Tao Mei

Recent advancements in text-to-image diffusion models have significantly transformed visual content generation, yet their application in specialized fields such as interior design remains underexplored. In this paper, we present…

Computer Vision and Pattern Recognition · Computer Science 2024-09-06 Zhaowei Wang , Ying Hao , Hao Wei , Qing Xiao , Lulu Chen , Yulong Li , Yue Yang , Tianyi Li