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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

Reconstructing 3D human-object interaction (HOI) from single-view RGB images is challenging due to the absence of depth information and potential occlusions. Existing methods simply predict the body poses merely rely on network training on…

Computer Vision and Pattern Recognition · Computer Science 2024-07-22 Yuhang Chen , Chenxing Wang

Demystifying complex human-ground interactions is essential for accurate and realistic 3D human motion reconstruction from RGB videos, as it ensures consistency between the humans and the ground plane. Prior methods have modeled…

Computer Vision and Pattern Recognition · Computer Science 2023-08-21 Sihan Ma , Qiong Cao , Hongwei Yi , Jing Zhang , Dacheng Tao

Generating 3D humans that functionally interact with 3D scenes remains an open problem with applications in embodied AI, robotics, and interactive content creation. The key challenge involves reasoning about both the semantics of functional…

Computer Vision and Pattern Recognition · Computer Science 2026-02-02 Jie Liu , Yu Sun , Alpar Cseke , Yao Feng , Nicolas Heron , Michael J. Black , Yan Zhang

Scenes are continuously undergoing dynamic changes in the real world. However, existing human-scene interaction generation methods typically treat the scene as static, which deviates from reality. Inspired by world models, we introduce…

Computer Vision and Pattern Recognition · Computer Science 2026-01-28 Yin Wang , Zhiying Leng , Haitian Liu , Frederick W. B. Li , Mu Li , Xiaohui Liang

This paper addresses the task of large-scale 3D scene reconstruction from long video sequences. Recent feed-forward reconstruction models have shown promising results by directly regressing 3D geometry from RGB images without explicit 3D…

Computer Vision and Pattern Recognition · Computer Science 2026-04-10 Tao Xie , Peishan Yang , Yudong Jin , Yingfeng Cai , Wei Yin , Weiqiang Ren , Qian Zhang , Wei Hua , Sida Peng , Xiaoyang Guo , Xiaowei Zhou

4D reconstruction of human-object interaction is critical for immersive VR/AR experience and human activity understanding. Recent advances still fail to recover fine geometry and texture results from sparse RGB inputs, especially under…

Computer Vision and Pattern Recognition · Computer Science 2021-08-04 Guoxing Sun , Xin Chen , Yizhang Chen , Anqi Pang , Pei Lin , Yuheng Jiang , Lan Xu , Jingya Wang , Jingyi Yu

Physical Human-Scene Interaction (HSI) plays a crucial role in numerous applications. However, existing HSI techniques are limited to specific object dynamics and privileged information, which prevents the development of more comprehensive…

Robotics · Computer Science 2024-11-14 Xinyu Xu , Yizheng Zhang , Yong-Lu Li , Lei Han , Cewu Lu

Digitizing the physical world into accurate simulation-ready virtual environments offers significant opportunities in a variety of fields such as augmented and virtual reality, gaming, and robotics. However, current 3D reconstruction and…

Computer Vision and Pattern Recognition · Computer Science 2025-10-08 Hongchi Xia , Chih-Hao Lin , Hao-Yu Hsu , Quentin Leboutet , Katelyn Gao , Michael Paulitsch , Benjamin Ummenhofer , Shenlong 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

Due to visual ambiguities and inter-person occlusions, existing human pose estimation methods cannot recover plausible close interactions from in-the-wild videos. Even state-of-the-art large foundation models~(\eg, SAM) cannot accurately…

Computer Vision and Pattern Recognition · Computer Science 2025-07-04 Buzhen Huang , Chen Li , Chongyang Xu , Dongyue Lu , Jinnan Chen , Yangang Wang , Gim Hee Lee

Reconstructing surgical scenes from monocular endoscopic video is critical for advancing robotic-assisted surgery. However, the application of state-of-the-art general-purpose reconstruction models is constrained by two key challenges: the…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Kaiyuan Xu , Fangzhou Hong , Daniel Elson , Baoru Huang

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 ReFlow, a unified framework for monocular dynamic scene reconstruction that learns 3D motion in a novel self-correction manner from raw video. Existing methods often suffer from incomplete scene initialization for dynamic…

Computer Vision and Pattern Recognition · Computer Science 2026-04-03 Yanzhe Liang , Ruijie Zhu , Hanzhi Chang , Zhuoyuan Li , Jiahao Lu , Tianzhu Zhang

High-quality 4D reconstruction of human performance with complex interactions to various objects is essential in real-world scenarios, which enables numerous immersive VR/AR applications. However, recent advances still fail to provide…

Computer Vision and Pattern Recognition · Computer Science 2021-05-03 Zhuo Su , Lan Xu , Dawei Zhong , Zhong Li , Fan Deng , Shuxue Quan , Lu Fang

Learning to generate diverse scene-aware and goal-oriented human motions in 3D scenes remains challenging due to the mediocre characteristics of the existing datasets on Human-Scene Interaction (HSI); they only have limited scale/quality…

Computer Vision and Pattern Recognition · Computer Science 2022-10-19 Zan Wang , Yixin Chen , Tengyu Liu , Yixin Zhu , Wei Liang , Siyuan Huang

Humans live within a 3D space and constantly interact with it to perform tasks. Such interactions involve physical contact between surfaces that is semantically meaningful. Our goal is to learn how humans interact with scenes and leverage…

Computer Vision and Pattern Recognition · Computer Science 2021-04-06 Mohamed Hassan , Partha Ghosh , Joachim Tesch , Dimitrios Tzionas , Michael J. Black

Synthesizing 3D human motion plays an important role in many graphics applications as well as understanding human activity. While many efforts have been made on generating realistic and natural human motion, most approaches neglect the…

Computer Vision and Pattern Recognition · Computer Science 2021-06-15 Jiashun Wang , Huazhe Xu , Jingwei Xu , Sifei Liu , Xiaolong Wang

Compositional scene reconstruction seeks to create object-centric representations rather than holistic scenes from real-world videos, which is natively applicable for simulation and interaction. Conventional compositional reconstruction…

Computer Vision and Pattern Recognition · Computer Science 2026-03-04 Chong Xia , Kai Zhu , Zizhuo Wang , Fangfu Liu , Zhizheng Zhang , Yueqi Duan

We present UniSH, a unified, feed-forward framework for joint metric-scale 3D scene and human reconstruction. A key challenge in this domain is the scarcity of large-scale, annotated real-world data, forcing a reliance on synthetic…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Mengfei Li , Peng Li , Zheng Zhang , Jiahao Lu , Chengfeng Zhao , Wei Xue , Qifeng Liu , Sida Peng , Wenxiao Zhang , Wenhan Luo , Yuan Liu , Yike Guo