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The 3D world limits the human body pose and the human body pose conveys information about the surrounding objects. Indeed, from a single image of a person placed in an indoor scene, we as humans are adept at resolving ambiguities of the…

Computer Vision and Pattern Recognition · Computer Science 2021-04-19 Zhenzhen Weng , Serena Yeung

Real-world human-built environments are highly dynamic, involving multiple humans and their complex interactions with surrounding objects. While 3D geometry modeling of such scenes is crucial for applications like AR/VR, gaming, and…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Sandika Biswas , Qianyi Wu , Biplab Banerjee , Hamid Rezatofighi

We present a novel method for recovering the absolute pose and shape of a human in a pre-scanned scene given a single image. Unlike previous methods that perform sceneaware mesh optimization, we propose to first estimate absolute position…

Computer Vision and Pattern Recognition · Computer Science 2023-06-07 Zehong Shen , Zhi Cen , Sida Peng , Qing Shuai , Hujun Bao , Xiaowei Zhou

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

To understand and analyze human behavior, we need to capture humans moving in, and interacting with, the world. Most existing methods perform 3D human pose estimation without explicitly considering the scene. We observe however that the…

Computer Vision and Pattern Recognition · Computer Science 2019-08-21 Mohamed Hassan , Vasileios Choutas , Dimitrios Tzionas , Michael J. Black

Animating realistic character interactions with the surrounding environment is important for autonomous agents in gaming, AR/VR, and robotics. However, current methods for human motion reconstruction struggle with accurately placing humans…

Computer Vision and Pattern Recognition · Computer Science 2025-10-20 Joshua Li , Brendan Chharawala , Chang Shu , Xue Bin Peng , Pengcheng Xi

Holistic 3D human-scene reconstruction is a crucial and emerging research area in robot perception. A key challenge in holistic 3D human-scene reconstruction is to generate a physically plausible 3D scene from a single monocular RGB image.…

Computer Vision and Pattern Recognition · Computer Science 2023-07-28 Sandika Biswas , Kejie Li , Biplab Banerjee , Subhasis Chaudhuri , Hamid Rezatofighi

We present HSImul3R, a unified framework for simulation-ready 3D reconstruction of human-scene interactions (HSI) from casual captures, including sparse-view images and monocular videos. Existing methods suffer from a perception-simulation…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Yukang Cao , Haozhe Xie , Fangzhou Hong , Long Zhuo , Zhaoxi Chen , Liang Pan , Ziwei Liu

Human-scene Interaction (HSI) generation is a challenging task and crucial for various downstream tasks. However, one of the major obstacles is its limited data scale. High-quality data with simultaneously captured human and 3D environments…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Xinpeng Liu , Haowen Hou , Yanchao Yang , Yong-Lu Li , Cewu Lu

Existing methods for reconstructing objects and humans from a monocular image suffer from severe mesh collisions and performance limitations for interacting occluding objects. This paper introduces a method to obtain a globally consistent…

Computer Vision and Pattern Recognition · Computer Science 2024-08-16 Sarthak Batra , Partha P. Chakrabarti , Simon Hadfield , Armin Mustafa

We propose a new 3D holistic++ scene understanding problem, which jointly tackles two tasks from a single-view image: (i) holistic scene parsing and reconstruction---3D estimations of object bounding boxes, camera pose, and room layout, and…

Computer Vision and Pattern Recognition · Computer Science 2019-09-05 Yixin Chen , Siyuan Huang , Tao Yuan , Siyuan Qi , Yixin Zhu , Song-Chun Zhu

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

Learning the prior knowledge of the 3D human-object spatial relation is crucial for reconstructing human-object interaction from images and understanding how humans interact with objects in 3D space. Previous works learn this prior from…

Computer Vision and Pattern Recognition · Computer Science 2024-08-01 Chaofan Huo , Ye Shi , Jingya Wang

We introduce (HPS) Human POSEitioning System, a method to recover the full 3D pose of a human registered with a 3D scan of the surrounding environment using wearable sensors. Using IMUs attached at the body limbs and a head mounted camera…

Computer Vision and Pattern Recognition · Computer Science 2021-04-01 Vladimir Guzov , Aymen Mir , Torsten Sattler , Gerard Pons-Moll

We present a method that infers spatial arrangements and shapes of humans and objects in a globally consistent 3D scene, all from a single image in-the-wild captured in an uncontrolled environment. Notably, our method runs on datasets…

Computer Vision and Pattern Recognition · Computer Science 2020-08-21 Jason Y. Zhang , Sam Pepose , Hanbyul Joo , Deva Ramanan , Jitendra Malik , Angjoo Kanazawa

Reconstructing textured 3D human models from a single image is fundamental for AR/VR and digital human applications. However, existing methods mostly focus on single individuals and thus fail in multi-human scenes, where naive composition…

Computer Vision and Pattern Recognition · Computer Science 2026-04-08 Gwanghyun Kim , Junghun James Kim , Suh Yoon Jeon , Jason Park , Se Young Chun

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

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

Creating scenes for captured motions that achieve realistic human-scene interaction is crucial for 3D animation in movies or video games. As character motion is often captured in a blue-screened studio without real furniture or objects in…

Computer Vision and Pattern Recognition · Computer Science 2024-05-22 Jianan Li , Tao Huang , Qingxu Zhu , Tien-Tsin Wong

Reconstructing physically plausible 3D human-scene interactions (HSI) from a single image currently presents a trade-off: optimization based methods offer accurate contact but are slow (~20s), while feed-forward approaches are fast yet lack…

Computer Vision and Pattern Recognition · Computer Science 2026-04-22 Pradyumna YM , Yuxuan Xue , Yue Chen , Nikita Kister , István Sárándi , Gerard Pons-Moll
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