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While current general-purpose 3D human models (e.g., SMPL-X) efficiently represent accurate human shape and pose, they lacks the ability to physically interact with the environment due to the kinematic nature. As a result, kinematic-based…

Computer Vision and Pattern Recognition · Computer Science 2025-08-13 Li Siyao , Yao Feng , Omid Taheri , Chen Change Loy , Michael J. Black

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-Scene Interaction (HSI) seeks to generate realistic human behaviors within complex environments, yet it faces significant challenges in handling long-horizon, high-level tasks and generalizing to unseen scenes. To address these…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Lingzhou Mu , Qiang Wang , Fan Jiang , Mengchao Wang , Yaqi Fan , Mu Xu , Kai Zhang

The physical properties of an object, such as mass, significantly affect how we manipulate it with our hands. Surprisingly, this aspect has so far been neglected in prior work on 3D motion synthesis. To improve the naturalness of the…

Computer Vision and Pattern Recognition · Computer Science 2023-12-25 Soshi Shimada , Franziska Mueller , Jan Bednarik , Bardia Doosti , Bernd Bickel , Danhang Tang , Vladislav Golyanik , Jonathan Taylor , Christian Theobalt , Thabo Beeler

Predicting the dynamics of interacting objects is essential for both humans and intelligent systems. However, existing approaches are limited to simplified, toy settings and lack generalizability to complex, real-world environments. Recent…

Computer Vision and Pattern Recognition · Computer Science 2025-04-07 Rick Akkerman , Haiwen Feng , Michael J. Black , Dimitrios Tzionas , Victoria Fernández Abrevaya

We present Uni-Inter, a unified framework for human motion generation that supports a wide range of interaction scenarios: including human-human, human-object, and human-scene-within a single, task-agnostic architecture. In contrast to…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Sheng Liu , Yuanzhi Liang , Jiepeng Wang , Sidan Du , Chi Zhang , Xuelong Li

Developing deep neural networks to generate 3D scenes is a fundamental problem in neural synthesis with immediate applications in architectural CAD, computer graphics, as well as in generating virtual robot training environments. This task…

Computer Vision and Pattern Recognition · Computer Science 2021-09-02 Haitao Yang , Zaiwei Zhang , Siming Yan , Haibin Huang , Chongyang Ma , Yi Zheng , Chandrajit Bajaj , Qixing Huang

Generating high-fidelity full-body human interactions with dynamic objects and static scenes remains a critical challenge in computer graphics and animation. Existing methods for human-object interaction often neglect scene context, leading…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Wei Yao , Yunlian Sun , Hongwen Zhang , Yebin Liu , Jinhui Tang

This paper addresses a novel task of anticipating 3D human-object interactions (HOIs). Most existing research on HOI synthesis lacks comprehensive whole-body interactions with dynamic objects, e.g., often limited to manipulating small or…

Computer Vision and Pattern Recognition · Computer Science 2023-09-01 Sirui Xu , Zhengyuan Li , Yu-Xiong Wang , Liang-Yan Gui

Remote telepresence via next-generation mixed reality platforms can provide higher levels of immersion for computer-mediated communications, allowing participants to engage in a wide spectrum of activities, previously not possible in 2D…

Human-Computer Interaction · Computer Science 2022-04-04 Mohammad Keshavarzi , Michael Zollhoefer , Allen Y. Yang , Patrick Peluse , Luisa Caldas

In this paper, we address the challenge of generating realistic 3D human motions for action classes that were never seen during the training phase. Our approach involves decomposing complex actions into simpler movements, specifically those…

Computer Vision and Pattern Recognition · Computer Science 2024-09-19 Lorenzo Mandelli , Stefano Berretti

Styled motion in-betweening is crucial for computer animation and gaming. However, existing methods typically encode motion styles by modeling whole-body motions, often overlooking the representation of individual body parts. This…

Computer Vision and Pattern Recognition · Computer Science 2025-08-14 Minyue Dai , Ke Fan , Bin Ji , Haoran Xu , Haoyu Zhao , Junting Dong , Jingbo Wang , Bo Dai

Complex scenes present significant challenges for predicting human behaviour due to the abundance of interaction information, such as human-human and humanenvironment interactions. These factors complicate the analysis and understanding of…

Computer Vision and Pattern Recognition · Computer Science 2026-04-02 Caiyi Sun , Yujing Sun , Xiao Han , Zemin Yang , Jiawei Liu , Xinge Zhu , Siu Ming Yiu , Yuexin Ma

We introduce a novel method for dynamic free-view synthesis of an ambient scenes from a monocular capture bringing a immersive quality to the viewing experience. Our method builds upon the recent advancements in 3D Gaussian Splatting (3DGS)…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Meng-Li Shih , Jia-Bin Huang , Changil Kim , Rajvi Shah , Johannes Kopf , Chen Gao

Novel-View Human Action Synthesis aims to synthesize the movement of a body from a virtual viewpoint, given a video from a real viewpoint. We present a novel 3D reasoning to synthesize the target viewpoint. We first estimate the 3D mesh of…

Computer Vision and Pattern Recognition · Computer Science 2020-10-09 Mohamed Ilyes Lakhal , Davide Boscaini , Fabio Poiesi , Oswald Lanz , Andrea Cavallaro

An emerging line of work has sought to generate plausible imagery from touch. Existing approaches, however, tackle only narrow aspects of the visuo-tactile synthesis problem, and lag significantly behind the quality of cross-modal synthesis…

Computer Vision and Pattern Recognition · Computer Science 2023-09-27 Fengyu Yang , Jiacheng Zhang , Andrew Owens

Synthesizing natural interactions between virtual humans and their 3D environments is critical for numerous applications, such as computer games and AR/VR experiences. Our goal is to synthesize humans interacting with a given 3D scene…

Computer Vision and Pattern Recognition · Computer Science 2022-07-27 Kaifeng Zhao , Shaofei Wang , Yan Zhang , Thabo Beeler , Siyu Tang

Contact-based grasp generation plays a crucial role in various applications. Recent methods typically focus on the geometric structure of objects, producing grasps with diverse hand poses and plausible contact points. However, these…

Graphics · Computer Science 2025-11-18 Zhuo Chen , Zhongqun Zhang , Yihua Cheng , Ales Leonardis , Hyung Jin Chang

Conventional methods for human motion synthesis are either deterministic or struggle with the trade-off between motion diversity and motion quality. In response to these limitations, we introduce MoFusion, i.e., a new…

Computer Vision and Pattern Recognition · Computer Science 2023-05-16 Rishabh Dabral , Muhammad Hamza Mughal , Vladislav Golyanik , Christian Theobalt

Current approaches for 3D human motion synthesis generate high quality animations of digital humans performing a wide variety of actions and gestures. However, a notable technological gap exists in addressing the complex dynamics of multi…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Anindita Ghosh , Rishabh Dabral , Vladislav Golyanik , Christian Theobalt , Philipp Slusallek
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