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We propose DiffusionDet, a new framework that formulates object detection as a denoising diffusion process from noisy boxes to object boxes. During the training stage, object boxes diffuse from ground-truth boxes to random distribution, and…

Computer Vision and Pattern Recognition · Computer Science 2023-08-22 Shoufa Chen , Peize Sun , Yibing Song , Ping Luo

The diffusion-based generative models have achieved remarkable success in text-based image generation. However, since it contains enormous randomness in generation progress, it is still challenging to apply such models for real-world visual…

Computer Vision and Pattern Recognition · Computer Science 2023-10-12 Chenyang Qi , Xiaodong Cun , Yong Zhang , Chenyang Lei , Xintao Wang , Ying Shan , Qifeng Chen

Recent text-to-video diffusion models have achieved impressive progress. In practice, users often desire the ability to control object motion and camera movement independently for customized video creation. However, current methods lack the…

Computer Vision and Pattern Recognition · Computer Science 2024-05-07 Shiyuan Yang , Liang Hou , Haibin Huang , Chongyang Ma , Pengfei Wan , Di Zhang , Xiaodong Chen , Jing Liao

Recent advancements in diffusion models have shown great promise in producing high-quality video content. However, efficiently training video diffusion models capable of integrating directional guidance and controllable motion intensity…

Computer Vision and Pattern Recognition · Computer Science 2025-02-06 Xuehai He , Shuohang Wang , Jianwei Yang , Xiaoxia Wu , Yiping Wang , Kuan Wang , Zheng Zhan , Olatunji Ruwase , Yelong Shen , Xin Eric Wang

Recent advances in customized video generation have enabled users to create videos tailored to both specific subjects and motion trajectories. However, existing methods often require complicated test-time fine-tuning and struggle with…

Computer Vision and Pattern Recognition · Computer Science 2024-10-18 Yujie Wei , Shiwei Zhang , Hangjie Yuan , Xiang Wang , Haonan Qiu , Rui Zhao , Yutong Feng , Feng Liu , Zhizhong Huang , Jiaxin Ye , Yingya Zhang , Hongming Shan

Despite remarkable achievements in video synthesis, achieving granular control over complex dynamics, such as nuanced movement among multiple interacting objects, still presents a significant hurdle for dynamic world modeling, compounded by…

Computer Vision and Pattern Recognition · Computer Science 2024-03-21 Pengxiang Li , Kai Chen , Zhili Liu , Ruiyuan Gao , Lanqing Hong , Guo Zhou , Hua Yao , Dit-Yan Yeung , Huchuan Lu , Xu Jia

Large-scale text-to-image diffusion models achieve unprecedented success in image generation and editing. However, how to extend such success to video editing is unclear. Recent initial attempts at video editing require significant…

Computer Vision and Pattern Recognition · Computer Science 2024-01-05 Wen Wang , Yan Jiang , Kangyang Xie , Zide Liu , Hao Chen , Yue Cao , Xinlong Wang , Chunhua Shen

Video diffusion models, trained on large-scale datasets, naturally capture correspondences of shared features across frames. Recent works have exploited this property for tasks such as optical flow prediction and tracking in a zero-shot…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Tianqi Zhang , Ziyi Wang , Wenzhao Zheng , Weiliang Chen , Yuanhui Huang , Zhengyang Huang , Jie Zhou , Jiwen Lu

The emergence of diffusion models has greatly propelled the progress in image and video generation. Recently, some efforts have been made in controllable video generation, including text-to-video generation and video motion control, among…

Computer Vision and Pattern Recognition · Computer Science 2024-05-02 Teng Hu , Jiangning Zhang , Ran Yi , Yating Wang , Hongrui Huang , Jieyu Weng , Yabiao Wang , Lizhuang Ma

Generating videos guided by camera trajectories poses significant challenges in achieving consistency and generalizability, particularly when both camera and object motions are present. Existing approaches often attempt to learn these…

Computer Vision and Pattern Recognition · Computer Science 2025-09-26 Guojun Lei , Chi Wang , Yikai Wang , Hong Li , Ying Song , Weiwei Xu

Generating realistic animated videos from static images is an important area of research in computer vision. Methods based on physical simulation and motion prediction have achieved notable advances, but they are often limited to specific…

Computer Vision and Pattern Recognition · Computer Science 2024-05-29 Qiang Wang , Minghua Liu , Junjun Hu , Fan Jiang , Mu Xu

With recent advances in image and video diffusion models for content creation, a plethora of techniques have been proposed for customizing their generated content. In particular, manipulating the cross-attention layers of Text-to-Image…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Saman Motamed , Wouter Van Gansbeke , Luc Van Gool

Multi-object tracking (MOT) is a challenging vision task that aims to detect individual objects within a single frame and associate them across multiple frames. Recent MOT approaches can be categorized into two-stage tracking-by-detection…

Computer Vision and Pattern Recognition · Computer Science 2024-02-22 Run Luo , Zikai Song , Lintao Ma , Jinlin Wei , Wei Yang , Min Yang

Controllable generation of 3D human motions becomes an important topic as the world embraces digital transformation. Existing works, though making promising progress with the advent of diffusion models, heavily rely on meticulously captured…

Computer Vision and Pattern Recognition · Computer Science 2024-01-25 Nhat M. Hoang , Kehong Gong , Chuan Guo , Michael Bi Mi

The generation of sounding videos has seen significant advancements with the advent of diffusion models. However, existing methods often lack the fine-grained control needed to generate viewpoint-specific content from larger, immersive…

Seamlessly moving objects within a scene is a common requirement for image editing, but it is still a challenge for existing editing methods. Especially for real-world images, the occlusion situation further increases the difficulty. The…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Zheng-Peng Duan , Jiawei Zhang , Siyu Liu , Zheng Lin , Chun-Le Guo , Dongqing Zou , Jimmy Ren , Chongyi Li

Large text-to-image diffusion models have achieved remarkable success in generating diverse, high-quality images. Additionally, these models have been successfully leveraged to edit input images by just changing the text prompt. But when…

Computer Vision and Pattern Recognition · Computer Science 2023-08-11 Anant Khandelwal

Video composition is the core task of video editing. Although image composition based on diffusion models has been highly successful, it is not straightforward to extend the achievement to video object composition tasks, which not only…

Computer Vision and Pattern Recognition · Computer Science 2024-06-25 Wei Wang , Yaosen Chen , Yuegen Liu , Qi Yuan , Shubin Yang , Yanru Zhang

Diffusion models are increasingly popular for generative tasks, including personalized composition of subjects and styles. While diffusion models can generate user-specified subjects performing text-guided actions in custom styles, they…

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