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The speed-precision trade-off is a critical problem for visual object tracking which usually requires low latency and deployment on constrained resources. Existing solutions for efficient tracking mainly focus on adopting light-weight…

Computer Vision and Pattern Recognition · Computer Science 2025-04-04 Jiawen Zhu , Xin Chen , Haiwen Diao , Shuai Li , Jun-Yan He , Chenyang Li , Bin Luo , Dong Wang , Huchuan Lu

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

Dense 3D tracking from monocular video is fundamental to dynamic scene understanding. While recent 3D foundation models provide reliable per-frame geometry, recovering object motion in this geometry remains challenging and benefits from…

Computer Vision and Pattern Recognition · Computer Science 2026-05-14 Jisu Nam , Jahyeok Koo , Soowon Son , Jaewoo Jung , Honggyu An , Junhwa Hur , Seungryong Kim

Video object removal and inpainting are critical tasks in the fields of computer vision and multimedia processing, aimed at restoring missing or corrupted regions in video sequences. Traditional methods predominantly rely on flow-based…

Computer Vision and Pattern Recognition · Computer Science 2025-08-19 Jie Liu , Zheng Hui

Object tracking is a fundamental task in computer vision, requiring the localization of objects of interest across video frames. Diffusion models have shown remarkable capabilities in visual generation, making them well-suited for…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Pha Nguyen , Ngan Le , Jackson Cothren , Alper Yilmaz , Khoa Luu

Diffusion Transformers (DiT)-based video generation models with 3D full attention exhibit strong generative capabilities. Trajectory control represents a user-friendly task in the field of controllable video generation. However, existing…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Cheng Lei , Jiayu Zhang , Yue Ma , Xinyu Wang , Long Chen , Liang Tang , Yiqiang Yan , Fei Su , Zhicheng Zhao

The motion transfer task aims to transfer motion from a source video to newly generated videos, requiring the model to decouple motion from appearance. Previous diffusion-based methods primarily rely on separate spatial and temporal…

Computer Vision and Pattern Recognition · Computer Science 2025-08-06 Qingyu Shi , Jianzong Wu , Jinbin Bai , Jiangning Zhang , Lu Qi , Yunhai Tong , Xiangtai Li

Many existing video inpainting algorithms utilize optical flows to construct the corresponding maps and then propagate pixels from adjacent frames to missing areas by mapping. Despite the effectiveness of the propagation mechanism, they…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Xian Wu , Chang Liu

Recent progress in diffusion models has significantly advanced the field of human image animation. While existing methods can generate temporally consistent results for short or regular motions, significant challenges remain, particularly…

Computer Vision and Pattern Recognition · Computer Science 2025-12-29 Shen Zheng , Jiaran Cai , Yuansheng Guan , Shenneng Huang , Xingpei Ma , Junjie Cao , Hanfeng Zhao , Qiang Zhang , Shunsi Zhang , Xiao-Ping Zhang

Video try-on stands as a promising area for its tremendous real-world potential. Previous research on video try-on has primarily focused on transferring product clothing images to videos with simple human poses, while performing poorly with…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Jun Zheng , Jing Wang , Fuwei Zhao , Xujie Zhang , Xiaodan Liang

As the task of 2D-to-3D reconstruction has gained significant attention in various real-world scenarios, it becomes crucial to be able to generate high-quality point clouds. Despite the recent success of deep learning models in generating…

Computer Vision and Pattern Recognition · Computer Science 2024-02-20 Yu Feng , Xing Shi , Mengli Cheng , Yun Xiong

Diffusion Transformers (DiT) have become the de-facto model for generating high-quality visual content like videos and images. A huge bottleneck is the attention mechanism where complexity scales quadratically with resolution and video…

Computer Vision and Pattern Recognition · Computer Science 2025-10-30 Ruichen Chen , Keith G. Mills , Liyao Jiang , Chao Gao , Di Niu

Video compositing combines live-action footage to create video production, serving as a crucial technique in video creation and film production. Traditional pipelines require intensive labor efforts and expert collaboration, resulting in…

Computer Vision and Pattern Recognition · Computer Science 2026-03-20 Shuzhou Yang , Xiaoyu Li , Xiaodong Cun , Guangzhi Wang , Lingen Li , Ying Shan , Jian Zhang

Motion transfer enables controllable video generation by transferring temporal dynamics from a reference video to synthesize a new video conditioned on a target caption. However, existing Diffusion Transformer (DiT)-based methods are…

Computer Vision and Pattern Recognition · Computer Science 2026-04-02 Samuel Teodoro , Yun Chen , Agus Gunawan , Soo Ye Kim , Jihyong Oh , Munchurl Kim

Recent Diffusion Transformers (e.g., DiT) have demonstrated their powerful effectiveness in generating high-quality 2D images. However, it is still being determined whether the Transformer architecture performs equally well in 3D shape…

Computer Vision and Pattern Recognition · Computer Science 2023-07-06 Shentong Mo , Enze Xie , Ruihang Chu , Lewei Yao , Lanqing Hong , Matthias Nießner , Zhenguo Li

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

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

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

In this paper, we consider the problem of long-term point tracking, which requires consistent identification of points across multiple frames in a video, despite changes in appearance, lighting, perspective, and occlusions. We target online…

Computer Vision and Pattern Recognition · Computer Science 2025-01-31 Görkay Aydemir , Xiongyi Cai , Weidi Xie , Fatma Güney

Generating temporally-consistent high-fidelity videos can be computationally expensive, especially over longer temporal spans. More-recent Diffusion Transformers (DiTs) -- despite making significant headway in this context -- have only…

Computer Vision and Pattern Recognition · Computer Science 2024-11-08 Kumara Kahatapitiya , Haozhe Liu , Sen He , Ding Liu , Menglin Jia , Chenyang Zhang , Michael S. Ryoo , Tian Xie
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