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When humans and robotic agents coexist in an environment, scene understanding becomes crucial for the agents to carry out various downstream tasks like navigation and planning. Hence, an agent must be capable of localizing and identifying…

Computer Vision and Pattern Recognition · Computer Science 2025-06-25 Mrunmai Vivek Phatak , Julian Lorenz , Nico Hörmann , Jörg Hähner , Rainer Lienhart

Designing and evaluating personalized and proactive assistant agents remains challenging due to the time, cost, and ethical concerns associated with human-in-the-loop experimentation. Existing Human-Computer Interaction (HCI) methods often…

Human-Computer Interaction · Computer Science 2025-11-25 Ziyi Xuan , Yiwen Wu , Xuhai Xu , Vinod Namboodiri , Mooi Choo Chuah , Yu Yang

Generating 3D scenes from human motion sequences supports numerous applications, including virtual reality and architectural design. However, previous auto-regression-based human-aware 3D scene generation methods have struggled to…

Computer Vision and Pattern Recognition · Computer Science 2024-08-21 Xiaolin Hong , Hongwei Yi , Fazhi He , Qiong Cao

Synthesizing realistic human-object interaction (HOI) is essential for 3D computer vision and robotics, underpinning animation and embodied control. Existing approaches often require manually specified intermediate waypoints and place all…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Hwanhee Jung , Seunggwan Lee , Jeongyoon Yoon , SeungHyeon Kim , Giljoo Nam , Qixing Huang , Sangpil Kim

Generating physically realistic humanoid-object interactions (HOI) is a fundamental challenge in robotics. Existing HOI generation approaches, such as diffusion-based models, often suffer from artifacts such as implausible contacts,…

Robotics · Computer Science 2025-08-21 Yuhang Lin , Yijia Xie , Jiahong Xie , Yuehao Huang , Ruoyu Wang , Jiajun Lv , Yukai Ma , Xingxing Zuo

Creating a diverse and comprehensive dataset of hand gestures for dynamic human-machine interfaces in the automotive domain can be challenging and time-consuming. To overcome this challenge, we propose using synthetic gesture datasets…

Computer Vision and Pattern Recognition · Computer Science 2024-08-05 Amr Gomaa , Robin Zitt , Guillermo Reyes , Antonio Krüger

This paper tackles the problem of physics-aware human motion synthesis in a dynamic scene. Unlike existing works which mainly tend to generate physically unrealistic motions due to limited contact modeling, typically restricted to hands, in…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Chaoyue Xing , Wei Mao , Miaomiao Liu

Hand-object interaction(HOI) is the fundamental link between human and environment, yet its dexterous and complex pose significantly challenges for gesture control. Despite significant advances in AI and robotics, enabling machines to…

Robotics · Computer Science 2025-07-11 Yongqi Tian , Xueyu Sun , Haoyuan He , Linji Hao , Ning Ding , Caigui Jiang

The way humans interact with each other, including interpersonal distances, spatial configuration, and motion, varies significantly across different situations. To enable machines to understand such complex, context-dependent behaviors, it…

Computer Vision and Pattern Recognition · Computer Science 2025-12-25 Jeonghyeon Na , Sangwon Baik , Inhee Lee , Junyoung Lee , Hanbyul Joo

Synthesizing human motions in 3D environments, particularly those with complex activities such as locomotion, hand-reaching, and human-object interaction, presents substantial demands for user-defined waypoints and stage transitions. These…

Computer Vision and Pattern Recognition · Computer Science 2024-10-10 Nan Jiang , Zimo He , Zi Wang , Hongjie Li , Yixin Chen , Siyuan Huang , Yixin Zhu

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

Confronting the challenges of data scarcity and advanced motion synthesis in human-scene interaction modeling, we introduce the TRUMANS dataset alongside a novel HSI motion synthesis method. TRUMANS stands as the most comprehensive…

Computer Vision and Pattern Recognition · Computer Science 2024-05-27 Nan Jiang , Zhiyuan Zhang , Hongjie Li , Xiaoxuan Ma , Zan Wang , Yixin Chen , Tengyu Liu , Yixin Zhu , Siyuan Huang

The ability to synthesize long-term human motion sequences in real-world scenes can facilitate numerous applications. Previous approaches for scene-aware motion synthesis are constrained by pre-defined target objects or positions and thus…

Computer Vision and Pattern Recognition · Computer Science 2022-05-27 Jingbo Wang , Yu Rong , Jingyuan Liu , Sijie Yan , Dahua Lin , Bo Dai

This paper presents a novel generative approach that outputs 3D indoor environments solely from a textual description of the scene. Current methods often treat scene synthesis as a mere layout prediction task, leading to rooms with…

Machine Learning · Computer Science 2025-02-12 Yao Wei , Matteo Toso , Pietro Morerio , Michael Ying Yang , Alessio Del Bue

Despite substantial progress in text-driven 3D human motion synthesis, generating realistic multi-person interaction sequences remains challenging. Notably, body inter-penetration is a pervasive issue from both data acquisition to the…

Computer Vision and Pattern Recognition · Computer Science 2026-05-04 Nan Lei , Yuan-Ming Li , Ling-An Zeng , Liang Xu , Zhi-Wei Xia , Hui-Wen Huang , Fa-Ting Hong , Wei-Shi Zheng

We present a novel method for populating 3D indoor scenes with virtual humans that can navigate in the environment and interact with objects in a realistic manner. Existing approaches rely on training sequences that contain captured human…

Computer Vision and Pattern Recognition · Computer Science 2023-08-22 Kaifeng Zhao , Yan Zhang , Shaofei Wang , Thabo Beeler , Siyu Tang

We present a physics-based character control framework for synthesizing human-scene interactions. Recent advances adopt physics simulation to mitigate artifacts produced by data-driven kinematic approaches. However, existing physics-based…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Liang Pan , Jingbo Wang , Buzhen Huang , Junyu Zhang , Haofan Wang , Xu Tang , Yangang Wang

Automatically generating interactive 3D environments is crucial for scaling up robotic data collection in simulation. While prior work has primarily focused on 3D asset placement, it often overlooks the physical relationships between…

Synthesizing semantic-aware, long-horizon, human-object interaction is critical to simulate realistic human behaviors. In this work, we address the challenging problem of generating synchronized object motion and human motion guided by…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Jiaman Li , Alexander Clegg , Roozbeh Mottaghi , Jiajun Wu , Xavier Puig , C. Karen Liu

Humans constantly interact with their surrounding environments. Current human-centric generative models mainly focus on synthesizing humans plausibly interacting with static scenes and objects, while the dynamic human action-reaction…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Liang Xu , Yizhou Zhou , Yichao Yan , Xin Jin , Wenhan Zhu , Fengyun Rao , Xiaokang Yang , Wenjun Zeng