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We introduce a novel semi-supervised video segmentation approach based on an efficient video representation, called as "super-trajectory". Each super-trajectory corresponds to a group of compact trajectories that exhibit consistent motion…

Computer Vision and Pattern Recognition · Computer Science 2017-07-25 Wenguan Wang , Jianbing Shen , Jianwen Xie , Fatih Porikli

Video prediction is commonly referred to as forecasting future frames of a video sequence provided several past frames thereof. It remains a challenging domain as visual scenes evolve according to complex underlying dynamics, such as the…

Computer Vision and Pattern Recognition · Computer Science 2021-05-12 Hafez Farazi , Jan Nogga , Sven Behnke

Accurately anticipating how complex, diverse scenes will evolve requires models that represent uncertainty, simulate along extended interaction chains, and efficiently explore many plausible futures. Yet most existing approaches rely on…

Computer Vision and Pattern Recognition · Computer Science 2026-04-13 Stefan Andreas Baumann , Jannik Wiese , Tommaso Martorella , Mahdi M. Kalayeh , Björn Ommer

Feed-forward multi-frame 3D reconstruction models often degrade on videos with object motion. Global-reference becomes ambiguous under multiple motions, while the local pointmap relies heavily on estimated relative poses and can drift,…

Computer Vision and Pattern Recognition · Computer Science 2026-02-06 Xingyu Miao , Weiguang Zhao , Tao Lu , Linning Xu , Mulin Yu , Yang Long , Jiangmiao Pang , Junting Dong

Generating human videos with realistic and controllable motions is a challenging task. While existing methods can generate visually compelling videos, they lack separate control over four key video elements: foreground subject, background…

Computer Vision and Pattern Recognition · Computer Science 2025-08-13 Jingyun Liang , Jingkai Zhou , Shikai Li , Chenjie Cao , Lei Sun , Yichen Qian , Weihua Chen , Fan Wang

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

Effective spatio-temporal representation is fundamental to modeling, understanding, and predicting dynamics in videos. The atomic unit of a video, the pixel, traces a continuous 3D trajectory over time, serving as the primitive element of…

Computer Vision and Pattern Recognition · Computer Science 2025-10-16 Xinhang Liu , Yuxi Xiao , Donny Y. Chen , Jiashi Feng , Yu-Wing Tai , Chi-Keung Tang , Bingyi Kang

Masked video modeling (MVM) has emerged as a simple and scalable self-supervised pretraining paradigm, but only encodes motion information implicitly, limiting the encoding of temporal dynamics in the learned representations. As a result,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Renaud Vandeghen , Fida Mohammad Thoker , Marc Van Droogenbroeck , Bernard Ghanem

In the absence of a mechanical stabilizer, the camera undergoes inevitable rotational dynamics during capturing, which induces perspective-based blur especially under long-exposure scenarios. From an optical standpoint, perspective-based…

Computer Vision and Pattern Recognition · Computer Science 2025-12-10 Tianchen Qiu , Qirun Zhang , Jiajian He , Zhengyue Zhuge , Jiahui Xu , Yueting Chen

World models have become crucial for autonomous driving, as they learn how scenarios evolve over time to address the long-tail challenges of the real world. However, current approaches relegate world models to limited roles: they operate…

Computer Vision and Pattern Recognition · Computer Science 2026-04-20 Tianze Xia , Yongkang Li , Lijun Zhou , Jingfeng Yao , Kaixin Xiong , Haiyang Sun , Bing Wang , Kun Ma , Guang Chen , Hangjun Ye , Wenyu Liu , Xinggang Wang

Modeling scenes using video generation models has garnered growing research interest in recent years. However, most existing approaches rely on perspective video models that synthesize only limited observations of a scene, leading to issues…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Yuheng Liu , Xin Lin , Xinke Li , Baihan Yang , Chen Wang , Kalyan Sunkavalli , Yannick Hold-Geoffroy , Hao Tan , Kai Zhang , Xiaohui Xie , Zifan Shi , Yiwei Hu

Current methods for trajectory prediction operate in supervised manners, and therefore require vast quantities of corresponding ground truth data for training. In this paper, we present a novel, label-free algorithm, AutoTrajectory, for…

Computer Vision and Pattern Recognition · Computer Science 2020-07-14 Yuexin Ma , Xinge ZHU , Xinjing Cheng , Ruigang Yang , Jiming Liu , Dinesh Manocha

Occlusion is a long-standing problem that causes many modern tracking methods to be erroneous. In this paper, we address the occlusion problem by exploiting the current and future possible locations of the target object from its past…

Computer Vision and Pattern Recognition · Computer Science 2020-10-16 Yuan Liu , Ruoteng Li , Robby T. Tan , Yu Cheng , Xiubao Sui

Video diffusion models (VDMs) have advanced significantly in recent years, enabling the generation of highly realistic videos and drawing the attention of the community in their potential as world simulators. However, despite their…

Computer Vision and Pattern Recognition · Computer Science 2025-04-07 Xindi Yang , Baolu Li , Yiming Zhang , Zhenfei Yin , Lei Bai , Liqian Ma , Zhiyong Wang , Jianfei Cai , Tien-Tsin Wong , Huchuan Lu , Xu Jia

We present a new test-time optimization method for estimating dense and long-range motion from a video sequence. Prior optical flow or particle video tracking algorithms typically operate within limited temporal windows, struggling to track…

Computer Vision and Pattern Recognition · Computer Science 2023-09-13 Qianqian Wang , Yen-Yu Chang , Ruojin Cai , Zhengqi Li , Bharath Hariharan , Aleksander Holynski , Noah Snavely

The prosperity of Multimodal Large Language Models (MLLMs) has stimulated the demand for video reasoning segmentation, which aims to segment video objects based on human instructions. Previous studies rely on unidirectional and implicit…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Jingnan Luo , Mingqi Gao , Jun Liu , Bin-Bin Gao , Feng Zheng

In this paper, we introduce an innovative approach for extracting trajectories from a camera sensor in GPS-denied environments, leveraging visual odometry. The system takes video footage captured by a forward-facing camera mounted on a…

Computer Vision and Pattern Recognition · Computer Science 2023-12-21 Abdulkadhem A. Abdulkadhem

Predicting future trajectories for other road agents is an essential task for autonomous vehicles. Established trajectory prediction methods primarily use agent tracks generated by a detection and tracking system and HD map as inputs. In…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Seokha Moon , Hyun Woo , Hongbeen Park , Haeji Jung , Reza Mahjourian , Hyung-gun Chi , Hyerin Lim , Sangpil Kim , Jinkyu Kim

As the demand grows within the construction industry for processes that are not only faster but also safer and more efficient, offsite construction has emerged as a solution, though it brings new safety risks due to the close interaction…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Mohammed Alduais , Xinming Li , Qipei Mei

While recent years have witnessed great progress on using diffusion models for video generation, most of them are simple extensions of image generation frameworks, which fail to explicitly consider one of the key differences between videos…

Computer Vision and Pattern Recognition · Computer Science 2024-07-31 Jingyun Liang , Yuchen Fan , Kai Zhang , Radu Timofte , Luc Van Gool , Rakesh Ranjan