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TROPHIES: Temporal Reconstruction of Places, Humans, and Cameras from Multi-view Videos

arXiv 2606.02350 ↗First posted 1 Jun 2026cs.CVcited by 0

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Abstract (arXiv)

Reconstructing humans and their surrounding environments in a globally consistent 4D space is essential for comprehensive perception. However, prior works typically assume single-view inputs or decouple humans, scenes, and cameras, making them unable to recover coherent geometry, stable motion, and physically aligned trajectories. These limitations motivate us to introduce a new task: unified human-scene-camera reconstruction from multi-view videos, which aims to jointly estimate dynamic humans, static scenes, and camera poses in one global coordinate frame. We propose TROPHIES--Temporal Reconstruction of Places, Humans, and Cameras from Multi-view Videos-a unified framework tailored for this task. TROPHIES features a Human Branch that models humans through temporal and spatial reasoning, and a Scene Branch that reconstructs static geometry with human-aware attention. A global alignment and optimization module couples both branches by enforcing scale consistency, contact priors, and cross-view temporal coherence. Experiments on EgoHuman and EgoExo4D demonstrate that TROPHIES achieves globally aligned, physically plausible 4D reconstructions and consistently outperforms existing paradigms in both global fidelity and human-scene consistency.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 47 of its 62 references that are in the map. First posted on arXiv 1 Jun 2026.

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47 of 62 references.

References · 47

  1. 2023Segment Anythingcited by 8,234
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  12. 2019Learning to Reconstruct 3D Human Pose and Shape via Model-fitting in the Loopcited by 627
35 more
  1. 2019VIBE: Video Inference for Human Body Pose and Shape Estimationcited by 620
  2. 2025Continuous 3D Perception Model with Persistent Statecited by 548
  3. 2023Ego-Exo4D: Understanding Skilled Human Activity from First- and Third-Person Perspectivescited by 490
  4. 2024MonST3R: A Simple Approach for Estimating Geometry in the Presence of Motioncited by 442
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  10. 2023TMR: Text-to-Motion Retrieval Using Contrastive 3D Human Motion Synthesiscited by 198
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  12. 2020Populating 3D Scenes by Learning Human-Scene Interactioncited by 164
  13. 2020Beyond Static Features for Temporally Consistent 3D Human Pose and Shape from a Videocited by 163
  14. 2021Human POSEitioning System (HPS): 3D Human Pose Estimation and Self-localization in Large Scenes from Body-Mounted Sensorscited by 137
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  23. 2025Easi3R: Estimating Disentangled Motion from DUSt3R Without Trainingcited by 91
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  35. 2024STAF: 3D Human Mesh Recovery from Video with Spatio-Temporal Alignment Fusioncited by 9

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  2. 20264D Human-Scene Reconstruction from Low-Overlap Captures
  3. 2024Guess The Unseen: Dynamic 3D Scene Reconstruction from Partial 2D Glimpses
  4. 2026DuoMo: Dual Motion Diffusion for World-Space Human Reconstruction
  5. 2026MotionMAR: Multi-scale Auto-Regressive Human Motion Reconstruction from Sparse Observations
  6. 20264DAnyone: Create Anyone in 4D from a Casual Monocular Video
  7. 2026Tele360: Real-Time Feed-Forward Human Reconstruction from Sparse Unposed Cameras
  8. 2026MotionCraft: Latent World Modeling with Sparse Attention for Visual Upscaling