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Generating realistic full-body motion interacting with objects is critical for applications in robotics, virtual reality, and human-computer interaction. While existing methods can generate full-body motion within 3D scenes, they often lack…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Kunal Bhosikar , Siddharth Katageri , Vivek Madhavaram , Kai Han , Charu Sharma

Recent advances in text-driven human motion generation enable models to synthesize realistic motion sequences from natural language descriptions. However, most existing approaches assume identity-neutral motion and generate movements using…

Computer Vision and Pattern Recognition · Computer Science 2026-04-29 Wenqi Jia , Zekun Li , Abhay Mittal , Chengcheng Tang , Chuan Guo , Lezi Wang , James Matthew Rehg , Lingling Tao , Size An

Simulating realistic interaction and motions for physics-based characters is of great interest for interactive applications, and automatic secondary character animation in the movie and video game industries. Recent works in reinforcement…

Computer Vision and Pattern Recognition · Computer Science 2023-11-07 Mohamed Younes , Ewa Kijak , Richard Kulpa , Simon Malinowski , Franck Multon

Hands are dexterous and highly versatile manipulators that are central to how humans interact with objects and their environment. Consequently, modeling realistic hand-object interactions, including the subtle motion of individual fingers,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Omid Taheri , Yi Zhou , Dimitrios Tzionas , Yang Zhou , Duygu Ceylan , Soren Pirk , Michael J. Black

Imitation learning from human motion capture (MoCap) data provides a promising way to train humanoid robots. However, due to differences in morphology, such as varying degrees of joint freedom and force limits, exact replication of human…

Robotics · Computer Science 2024-10-04 Wenshuai Zhao , Yi Zhao , Joni Pajarinen , Michael Muehlebach

Despite significant advances in video generation, synthesizing physically plausible human actions remains a persistent challenge, particularly in modeling fine-grained semantics and complex temporal dynamics. For instance, generating…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Dian Shao , Mingfei Shi , Shengda Xu , Haodong Chen , Yongle Huang , Binglu Wang

Human motion generation has been widely studied due to its crucial role in areas such as digital humans and humanoid robot control. However, many current motion generation approaches disregard physics constraints, frequently resulting in…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Zhuo Li , Mingshuang Luo , Ruibing Hou , Xin Zhao , Hao Liu , Hong Chang , Zimo Liu , Chen Li

We present a new trainable system for physically plausible markerless 3D human motion capture, which achieves state-of-the-art results in a broad range of challenging scenarios. Unlike most neural methods for human motion capture, our…

Computer Vision and Pattern Recognition · Computer Science 2021-05-04 Soshi Shimada , Vladislav Golyanik , Weipeng Xu , Patrick Pérez , Christian Theobalt

In many contexts, creating mappings for gestural interactions can form part of an artistic process. Creators seeking a mapping that is expressive, novel, and affords them a sense of authorship may not know how to program it up in a signal…

Human-Computer Interaction · Computer Science 2021-06-17 Tim Murray-Browne , Panagiotis Tigas

We introduce a method to synthesize animator guided human motion across 3D scenes. Given a set of sparse (3 or 4) joint locations (such as the location of a person's hand and two feet) and a seed motion sequence in a 3D scene, our method…

Computer Vision and Pattern Recognition · Computer Science 2025-02-04 Aymen Mir , Xavier Puig , Angjoo Kanazawa , Gerard Pons-Moll

We present a system that allows users to visualize complex human motion via 3D motion sculptures---a representation that conveys the 3D structure swept by a human body as it moves through space. Given an input video, our system computes the…

Human-Computer Interaction · Computer Science 2019-01-03 Xiuming Zhang , Tali Dekel , Tianfan Xue , Andrew Owens , Qiurui He , Jiajun Wu , Stefanie Mueller , William T. Freeman

This paper addresses the challenge of learning semantically and functionally meaningful 3D motion priors from real-world videos, in order to enable prediction of future 3D scene motion from a single input image. We propose a novel…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Jiahui Lei , Kyle Genova , George Kopanas , Noah Snavely , Leonidas Guibas

High-fidelity haptic feedback is essential for immersive virtual environments, yet authoring realistic tactile textures remains a significant bottleneck for designers. We introduce HapticMatch, a visual-to-tactile generation framework…

Human-Computer Interaction · Computer Science 2026-01-26 Mingxin Zhang , Yu Yao , Yasutoshi Makino , Hiroyuki Shinoda , Masashi Sugiyama

Real-time synthesis of physically plausible human interactions remains a critical challenge for immersive VR/AR systems and humanoid robotics. While existing methods demonstrate progress in kinematic motion generation, they often fail to…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Kaiyang Ji , Ye Shi , Zichen Jin , Kangyi Chen , Lan Xu , Yuexin Ma , Jingyi Yu , Jingya Wang

Achieving realistic simulations of humans interacting with a wide range of objects has long been a fundamental goal. Extending physics-based motion imitation to complex human-object interactions (HOIs) is challenging due to intricate…

Computer Vision and Pattern Recognition · Computer Science 2026-02-03 Sirui Xu , Hung Yu Ling , Yu-Xiong Wang , Liang-Yan Gui

We address the challenging problem of robotic grasping and manipulation in the presence of uncertainty. This uncertainty is due to noisy sensing, inaccurate models and hard-to-predict environment dynamics. We quantify the importance of…

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

Modeling and generating human reactions poses a significant challenge with broad applications for computer vision and human-computer interaction. Existing methods either treat multiple individuals as a single entity, directly generating…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Xiyan Xu , Sirui Xu , Yu-Xiong Wang , Liang-Yan Gui

Interactive applications demand believable characters that respond naturally to dynamic environments. Traditional character animation techniques often struggle to handle arbitrary situations, leading to a growing trend of dynamically…

Graphics · Computer Science 2025-10-28 Jose Luis Ponton , Sheldon Andrews , Carlos Andujar , Nuria Pelechano

Recent advances in 3D content generation have amplified demand for dynamic models that are both visually realistic and physically consistent. However, state-of-the-art video diffusion models frequently produce implausible results such as…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Siwei Meng , Yawei Luo , Ping Liu