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Simulation is a central tool for scalable robot learning, but its effectiveness depends on the quality of object assets. While modern 3D datasets provide rich geometric and kinematic representations, they typically lack the physical…

Robotics · Computer Science 2026-05-20 Anh-Quan Pham

Video generative models pre-trained on large-scale internet datasets have achieved remarkable success, excelling at producing realistic synthetic videos. However, they often generate clips based on static prompts (e.g., text or images),…

Computer Vision and Pattern Recognition · Computer Science 2025-02-13 Haoran He , Yang Zhang , Liang Lin , Zhongwen Xu , Ling Pan

Monocular dynamic reconstruction is a challenging and long-standing vision problem due to the highly ill-posed nature of the task. Existing approaches depend on templates, are effective only in quasi-static scenes, or fail to model 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Qianqian Wang , Vickie Ye , Hang Gao , Weijia Zeng , Jake Austin , Zhengqi Li , Angjoo Kanazawa

High-quality reconstruction of controllable 3D head avatars from 2D videos is highly desirable for virtual human applications in movies, games, and telepresence. Neural implicit fields provide a powerful representation to model 3D head…

Computer Vision and Pattern Recognition · Computer Science 2023-04-24 Chuhan Chen , Matthew O'Toole , Gaurav Bharaj , Pablo Garrido

As interest grows in world models that predict future states from current observations and actions, accurately modeling part-level dynamics has become increasingly relevant for various applications. Existing approaches, such as…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Mingju Gao , Yike Pan , Huan-ang Gao , Zongzheng Zhang , Wenyi Li , Hao Dong , Hao Tang , Li Yi , Hao Zhao

People interact with the real-world largely dependent on visual signal, which are ubiquitous and illustrate detailed demonstrations. In this paper, we explore utilizing visual signals as a new interface for models to interact with the…

Computer Vision and Pattern Recognition · Computer Science 2025-03-20 Wentao Zhang , Junliang Guo , Tianyu He , Li Zhao , Linli Xu , Jiang Bian

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

This paper addresses the task of modeling Deformable Linear Objects (DLOs), such as ropes and cables, during dynamic motion over long time horizons. This task presents significant challenges due to the complex dynamics of DLOs. To address…

Robotics · Computer Science 2025-03-10 Yizhou Chen , Yiting Zhang , Zachary Brei , Tiancheng Zhang , Yuzhen Chen , Julie Wu , Ram Vasudevan

We have seen much recent progress in rigid object manipulation, but interaction with deformable objects has notably lagged behind. Due to the large configuration space of deformable objects, solutions using traditional modelling approaches…

Robotics · Computer Science 2018-10-09 Jan Matas , Stephen James , Andrew J. Davison

State-of-the-art video generation models produce remarkable photorealism, but they lack the precise control required to align generated content with specific scene requirements. Furthermore, without an underlying explicit geometry, these…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Dana Cohen-Bar , Ido Sobol , Raphael Bensadoun , Shelly Sheynin , Oran Gafni , Or Patashnik , Daniel Cohen-Or , Amit Zohar

Multi-task learning of deformable object manipulation is a challenging problem in robot manipulation. Most previous works address this problem in a goal-conditioned way and adapt goal images to specify different tasks, which limits the…

Robotics · Computer Science 2024-01-30 Yuhong Deng , Kai Mo , Chongkun Xia , Xueqian Wang

We introduce a method to generate videos of dynamic virtual objects plausibly interacting via collisions with a still image's environment. Given a starting trajectory, physically simulated with the estimated geometry of a single, static…

Computer Vision and Pattern Recognition · Computer Science 2019-08-27 Carlo Innamorati , Bryan Russell , Danny M. Kaufman , and Niloy J. Mitra

Simulating physically realistic garment deformations is an essential task for virtual immersive experience, which is often achieved by physics simulation methods. However, these methods are typically time-consuming, computationally…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Chengfeng Zhao , Junbo Qi , Yulou Liu , Zhiyang Dou , Minchen Li , Taku Komura , Ziwei Liu , Wenping Wang , Yuan Liu

In this work we present a novel approach for computing correspondences between non-rigid objects, by exploiting a reduced representation of deformation fields. Different from existing works that represent deformation fields by training a…

Computer Vision and Pattern Recognition · Computer Science 2022-11-29 Ramana Sundararaman , Riccardo Marin , Emanuele Rodola , Maks Ovsjanikov

Given a source image and a driving video depicting the same object type, the motion transfer task aims to generate a video by learning the motion from the driving video while preserving the appearance from the source image. In this paper,…

Computer Vision and Pattern Recognition · Computer Science 2022-04-12 Jiale Tao , Biao Wang , Borun Xu , Tiezheng Ge , Yuning Jiang , Wen Li , Lixin Duan

The landscape of video generation is shifting, from a focus on generating visually appealing clips to building virtual environments that support interaction and maintain physical plausibility. These developments point toward the emergence…

Artificial Intelligence · Computer Science 2026-02-09 Jingtong Yue , Ziqi Huang , Zhaoxi Chen , Xintao Wang , Pengfei Wan , Ziwei Liu

We propose novel motion representations for animating articulated objects consisting of distinct parts. In a completely unsupervised manner, our method identifies object parts, tracks them in a driving video, and infers their motions by…

Computer Vision and Pattern Recognition · Computer Science 2021-04-26 Aliaksandr Siarohin , Oliver J. Woodford , Jian Ren , Menglei Chai , Sergey Tulyakov

World models serve as essential building blocks toward Artificial General Intelligence (AGI), enabling intelligent agents to predict future states and plan actions by simulating complex physical interactions. However, existing interactive…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Junyi Chen , Haoyi Zhu , Xianglong He , Yifan Wang , Jianjun Zhou , Wenzheng Chang , Yang Zhou , Zizun Li , Zhoujie Fu , Jiangmiao Pang , Tong He

The ability to create realistic, animatable and relightable head avatars from casual video sequences would open up wide ranging applications in communication and entertainment. Current methods either build on explicit 3D morphable meshes…

Computer Vision and Pattern Recognition · Computer Science 2023-03-01 Yufeng Zheng , Wang Yifan , Gordon Wetzstein , Michael J. Black , Otmar Hilliges

Fiducial markers have been broadly used to identify objects or embed messages that can be detected by a camera. Primarily, existing detection methods assume that markers are printed on ideally planar surfaces. Markers often fail to be…

Computer Vision and Pattern Recognition · Computer Science 2022-06-17 Mustafa B. Yaldiz , Andreas Meuleman , Hyeonjoong Jang , Hyunho Ha , Min H. Kim