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We tackle the challenging task of generating complete 3D facial animations for two interacting, co-located participants from a mixed audio stream. While existing methods often produce disembodied "talking heads" akin to a video conference…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Mengyi Shan , Shouchieh Chang , Ziqian Bai , Shichen Liu , Yinda Zhang , Luchuan Song , Rohit Pandey , Sean Fanello , Zeng Huang

Social interaction is a fundamental aspect of human behavior and communication. The way individuals position themselves in relation to others, also known as proxemics, conveys social cues and affects the dynamics of social interaction.…

Computer Vision and Pattern Recognition · Computer Science 2023-12-14 Lea Müller , Vickie Ye , Georgios Pavlakos , Michael Black , Angjoo Kanazawa

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

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

We propose a novel method for spatiotemporal multi-camera calibration using freely moving people in multiview videos. Since calibrating multiple cameras and finding matches across their views are inherently interdependent, performing both…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Sang-Eun Lee , Ko Nishino , Shohei Nobuhara

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

Recovering multi-person 3D poses with absolute scales from a single RGB image is a challenging problem due to the inherent depth and scale ambiguity from a single view. Addressing this ambiguity requires to aggregate various cues over the…

Computer Vision and Pattern Recognition · Computer Science 2020-08-27 Jianan Zhen , Qi Fang , Jiaming Sun , Wentao Liu , Wei Jiang , Hujun Bao , Xiaowei Zhou

Human motion capture either requires multi-camera systems or is unreliable when using single-view input due to depth ambiguities. Meanwhile, mirrors are readily available in urban environments and form an affordable alternative by recording…

Computer Vision and Pattern Recognition · Computer Science 2024-05-17 Daniel Ajisafe , James Tang , Shih-Yang Su , Bastian Wandt , Helge Rhodin

Accurately reconstructing human behavior in close-interaction scenarios is crucial for enabling realistic virtual interactions in augmented reality, precise motion analysis in sports, and natural collaborative behavior in human-robot tasks.…

Computer Vision and Pattern Recognition · Computer Science 2026-04-16 Qi Xia , Peishan Cong , Ziyi Wang , Yujing Sun , Qin Sun , Xinge Zhu , Mao Ye , Ruigang Yang , Yuexin Ma

Eye movements provide a window into human behaviour, attention, and interaction dynamics. Challenges in real-world, multi-person environments have, however, restrained eye-tracking research predominantly to single-person, in-lab settings.…

Human-Computer Interaction · Computer Science 2025-05-27 Shreshth Saxena , Areez Visram , Neil Lobo , Zahid Mirza , Mehak Rafi Khan , Biranugan Pirabaharan , Alexander Nguyen , Lauren K. Fink

Many popular tourist landmarks are captured in a multitude of online, public photos. These photos represent a sparse and unstructured sampling of the plenoptic function for a particular scene. In this paper,we present a new approach to…

Computer Vision and Pattern Recognition · Computer Science 2020-07-31 Zhengqi Li , Wenqi Xian , Abe Davis , Noah Snavely

This paper presents a novel method for generating diverse 3D human poses in scenes with semantic control. Existing methods heavily rely on the human-scene interaction dataset, resulting in a limited diversity of the generated human poses.…

Computer Vision and Pattern Recognition · Computer Science 2024-06-11 Bowen Dang , Xi Zhao

We present a method for teaching machines to understand and model the underlying spatial common sense of diverse human-object interactions in 3D in a self-supervised way. This is a challenging task, as there exist specific manifolds of the…

Computer Vision and Pattern Recognition · Computer Science 2023-09-06 Sookwan Han , Hanbyul Joo

In this work, we consider the problem of estimating the 3D position of multiple humans in a scene as well as their body shape and articulation from a single RGB video recorded with a static camera. In contrast to expensive marker-based or…

Computer Vision and Pattern Recognition · Computer Science 2023-03-28 Diogo Luvizon , Marc Habermann , Vladislav Golyanik , Adam Kortylewski , Christian Theobalt

We propose Panoptic Lifting, a novel approach for learning panoptic 3D volumetric representations from images of in-the-wild scenes. Once trained, our model can render color images together with 3D-consistent panoptic segmentation from…

Computer Vision and Pattern Recognition · Computer Science 2022-12-21 Yawar Siddiqui , Lorenzo Porzi , Samuel Rota Buló , Norman Müller , Matthias Nießner , Angela Dai , Peter Kontschieder

A long-standing challenge in scene analysis is the recovery of scene arrangements under moderate to heavy occlusion, directly from monocular video. While the problem remains a subject of active research, concurrent advances have been made…

Graphics · Computer Science 2019-07-19 Aron Monszpart , Paul Guerrero , Duygu Ceylan , Ersin Yumer , Niloy J. Mitra

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

This paper proposes a novel application system for the generation of three-dimensional (3D) character animation driven by markerless human body motion capturing. The entire pipeline of the system consists of five stages: 1) the capturing of…

Computer Vision and Pattern Recognition · Computer Science 2022-12-13 Jinbao Wang , Ke Lu , Jian Xue

Tracking body and hand motions in the 3D space is essential for social and self-presence in augmented and virtual environments. Unlike the popular 3D pose estimation setting, the problem is often formulated as inside-out tracking based on…

Computer Vision and Pattern Recognition · Computer Science 2020-12-08 Mathias Parger , Chengcheng Tang , Yuanlu Xu , Christopher Twigg , Lingling Tao , Yijing Li , Robert Wang , Markus Steinberger

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