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Related papers: PhysHanDI: Physics-Based Reconstruction of Hand-De…

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World models for deformable objects should recover not only geometry and appearance, but also underlying physical dynamics, interaction grounding, and material behavior. Learning such a model from real videos is challenging because…

Computer Vision and Pattern Recognition · Computer Science 2026-05-21 Can Li , Zhoujian Li , Ren Li , Jie Gu , Lei Lei , Jingmin Chen , Lei Sun

The credibility and practicality of a reconstructed hand-object interaction sequence depend largely on its physical plausibility. However, due to high occlusions during hand-object interaction, physical plausibility remains a challenging…

Computer Vision and Pattern Recognition · Computer Science 2024-05-21 Haowen Luo , Yunze Liu , Li Yi

Hands are the main medium when people interact with the world. Generating proper 3D motion for hand-object interaction is vital for applications such as virtual reality and robotics. Although grasp tracking or object manipulation synthesis…

Computer Vision and Pattern Recognition · Computer Science 2024-01-30 Yuze Hao , Jianrong Zhang , Tao Zhuo , Fuan Wen , Hehe Fan

In this paper, we presented a new method for deformation control of deformable objects, which utilizes both visual and tactile feedback. At present, manipulation of deformable objects is basically formulated by assuming positional…

Robotics · Computer Science 2021-06-01 Yuhao Guo , Xin Jiang , Yunhui Liu

Accurate object geometry estimation is essential for many downstream tasks, including robotic manipulation and physical interaction. Although vision is the dominant modality for shape perception, it becomes unreliable under occlusions or…

Computer Vision and Pattern Recognition · Computer Science 2026-04-13 Langzhe Gu , Hung-Jui Huang , Mohamad Qadri , Michael Kaess , Wenzhen Yuan

Accurate 3D reconstruction of the hand and object shape from a hand-object image is important for understanding human-object interaction as well as human daily activities. Different from bare hand pose estimation, hand-object interaction…

Computer Vision and Pattern Recognition · Computer Science 2021-04-21 Yujin Chen , Zhigang Tu , Di Kang , Ruizhi Chen , Linchao Bao , Zhengyou Zhang , Junsong Yuan

We interact with the world with our hands and see it through our own (egocentric) perspective. A holistic 3Dunderstanding of such interactions from egocentric views is important for tasks in robotics, AR/VR, action recognition and motion…

Realistic object interactions are crucial for creating immersive virtual experiences, yet synthesizing realistic 3D object dynamics in response to novel interactions remains a significant challenge. Unlike unconditional or text-conditioned…

Computer Vision and Pattern Recognition · Computer Science 2024-10-08 Tianyuan Zhang , Hong-Xing Yu , Rundi Wu , Brandon Y. Feng , Changxi Zheng , Noah Snavely , Jiajun Wu , William T. Freeman

3D hand-object interaction data is scarce due to the hardware constraints in scaling up the data collection process. In this paper, we propose HOIDiffusion for generating realistic and diverse 3D hand-object interaction data. Our model is a…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Mengqi Zhang , Yang Fu , Zheng Ding , Sifei Liu , Zhuowen Tu , Xiaolong Wang

Most RGB-based hand-object reconstruction methods rely on object templates, while template-free methods typically assume full object visibility. This assumption often breaks in real-world settings, where fixed camera viewpoints and static…

Computer Vision and Pattern Recognition · Computer Science 2025-08-08 Shibo Wang , Haonan He , Maria Parelli , Christoph Gebhardt , Zicong Fan , Jie Song

Reconstructing metrically accurate humans and their surrounding scenes from a single image is crucial for virtual reality, robotics, and comprehensive 3D scene understanding. However, existing methods struggle with depth ambiguity,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Pradyumna Yalandur Muralidhar , Yuxuan Xue , Xianghui Xie , Margaret Kostyrko , Gerard Pons-Moll

Accurate modelling of object deformations is crucial for a wide range of robotic manipulation tasks, where interacting with soft or deformable objects is essential. Current methods struggle to generalise to unseen forces or adapt to new…

Robotics · Computer Science 2025-05-20 Sean M. V. Collins , Brendan Tidd , Mahsa Baktashmotlagh , Peyman Moghadam

Since humans interact with diverse objects every day, the holistic 3D capture of these interactions is important to understand and model human behaviour. However, most existing methods for hand-object reconstruction from RGB either assume…

Computer Vision and Pattern Recognition · Computer Science 2023-12-01 Zicong Fan , Maria Parelli , Maria Eleni Kadoglou , Muhammed Kocabas , Xu Chen , Michael J. Black , Otmar Hilliges

We present ViTaM-D, a novel visual-tactile framework for reconstructing dynamic hand-object interaction with distributed tactile sensing to enhance contact modeling. Existing methods, relying solely on visual inputs, often fail to capture…

Computer Vision and Pattern Recognition · Computer Science 2025-07-10 Zhenjun Yu , Wenqiang Xu , Pengfei Xie , Yutong Li , Brian W. Anthony , Zhuorui Zhang , Cewu Lu

Hand manipulating objects is an important interaction motion in our daily activities. We faithfully reconstruct this motion with a single RGBD camera by a novel deep reinforcement learning method to leverage physics. Firstly, we propose…

Computer Vision and Pattern Recognition · Computer Science 2024-05-07 Haoyu Hu , Xinyu Yi , Zhe Cao , Jun-Hai Yong , Feng Xu

Recent hand-object interaction datasets show limited real object variability and rely on fitting the MANO parametric model to obtain groundtruth hand shapes. To go beyond these limitations and spur further research, we introduce the SHOWMe…

Computer Vision and Pattern Recognition · Computer Science 2023-09-20 Anilkumar Swamy , Vincent Leroy , Philippe Weinzaepfel , Fabien Baradel , Salma Galaaoui , Romain Bregier , Matthieu Armando , Jean-Sebastien Franco , Gregory Rogez

We propose a multimodal, physically grounded approach for metric-scale amodal object reconstruction and pose estimation under severe hand occlusion. Unlike prior occlusion-aware 3D generation methods that rely only on vision, we leverage…

Computer Vision and Pattern Recognition · Computer Science 2026-04-13 Gabriele Mario Caddeo , Pasquale Marra , Lorenzo Natale

This work addresses the problem of recovering complete, simulatable object geometry from reconstructed real-world scenes, enabling physics-based interaction with objects embedded in the scene. While modern multi-view reconstruction methods…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Xin Dong , Weijian Deng , Lihan Zhang , Tianru Dai , Wenfeng Deng , Yansong Tang

This paper introduces the first text-guided work for generating the sequence of hand-object interaction in 3D. The main challenge arises from the lack of labeled data where existing ground-truth datasets are nowhere near generalizable in…

Computer Vision and Pattern Recognition · Computer Science 2024-04-03 Junuk Cha , Jihyeon Kim , Jae Shin Yoon , Seungryul Baek

Recent advances in video generative models enable the synthesis of realistic human-object interaction videos across a wide range of scenarios and object categories, including complex dexterous manipulations that are difficult to capture…

Computer Vision and Pattern Recognition · Computer Science 2026-04-23 Hyeonwoo Kim , Jeonghwan Kim , Kyungwon Cho , Hanbyul Joo