Panoptic Studio: A Massively Multiview System for Social Interaction Capture
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Abstract (arXiv)
We present an approach to capture the 3D motion of a group of people engaged in a social interaction. The core challenges in capturing social interactions are: (1) occlusion is functional and frequent; (2) subtle motion needs to be measured over a space large enough to host a social group; (3) human appearance and configuration variation is immense; and (4) attaching markers to the body may prime the nature of interactions. The Panoptic Studio is a system organized around the thesis that social interactions should be measured through the integration of perceptual analyses over a large variety of view points. We present a modularized system designed around this principle, consisting of integrated structural, hardware, and software innovations. The system takes, as input, 480 synchronized video streams of multiple people engaged in social activities, and produces, as output, the labeled time-varying 3D structure of anatomical landmarks on individuals in the space. Our algorithm is designed to fuse the "weak" perceptual processes in the large number of views by progressively generating skeletal proposals from low-level appearance cues, and a framework for temporal refinement is also presented by associating body parts to reconstructed dense 3D trajectory stream. Our system and method are the first in reconstructing full body motion of more than five people engaged in social interactions without using markers. We also empirically demonstrate the impact of the number of views in achieving this goal.
Key facts. Cited by 173 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Dec 2016.
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Citing papers per year: 2021: 46; 2022: 24; 2023: 21; 2024: 32; 2025: 26; 2026: 24.
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50 most cited of 173 All 173 (JSON)
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50 newest of 173 All 173 (JSON)
- 2021Common Objects in 3D: Large-Scale Learning and Evaluation of Real-life 3D Category Reconstructioncited by 646
- 2023Ego-Exo4D: Understanding Skilled Human Activity from First- and Third-Person Perspectivescited by 477
- 2021H2O: Two Hands Manipulating Objects for First Person Interaction Recognitioncited by 251
- 2023BEDLAM: A Synthetic Dataset of Bodies Exhibiting Detailed Lifelike Animated Motioncited by 229
- 2021AGORA: Avatars in Geography Optimized for Regression Analysiscited by 203
- 2021Neural Articulated Radiance Fieldcited by 196
- 2021FrankMocap: A Monocular 3D Whole-Body Pose Estimation System via Regression and Integrationcited by 168
- 2021EgoBody: Human Body Shape and Motion of Interacting People from Head-Mounted Devicescited by 136
- 2024WiLoR: End-to-end 3D Hand Localization and Reconstruction in-the-wildcited by 117
- 2024Nymeria: A Massive Collection of Multimodal Egocentric Daily Motion in the Wildcited by 109
- 2023DNA-Rendering: A Diverse Neural Actor Repository for High-Fidelity Human-centric Renderingcited by 103
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12 most cited of 167 All 167 (JSON)
- 2026Generative Interactions: Weaving Multiparty Human Motion with Bilevel Latent Dynamics29 Sep 2026
- 2026Gaussian Splatting-based Volumetric Video Compression with Sparse 4D Anchors27 Sep 2026
- 2026ADATEX4D: adaptive texture capacity allocation for 4D gaussian splatting24 Sep 2026
- 2026STA-TFM: Spatio-Temporal Aggregation Across Views TransForMer for Pose Estimation21 Sep 2026
- 2026Racing in Volume with Flow Ensembles14 Sep 2026
- 2026UniFusion: Sparse-View 4D Reconstruction via Unified Spatio-temporal Depth Alignment5 Sep 2026
- 2026SICAGE: Speaker-Independent Culture-Aware Gesture Generation using TED4C-L Dataset29 Jun 2026
- 2026GS-NFS: Bandwidth-adaptive Streaming of Dynamic Gaussian Splats and Point Clouds4 Jun 2026
- 2026DyaPlex: Full-Duplex Speech-Motion Model for Dyadic Interaction2 Jun 2026
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