CHOIR: Contact-aware 4D Hand-Object Interaction Reconstruction

• URL: http://arxiv.org/abs/2605.20992v2
• Date: Thu, 21 May 2026 13:57:17 GMT
• Title: CHOIR: Contact-aware 4D Hand-Object Interaction Reconstruction
• Abstract summary: We present CHOIR, a Contact-aware HOI Reconstruction framework for a monocular camera.<n>ChoIR first initializes a coarse, contact-agnostic 4D HOI sequence from open-world visual priors.<n>It then introduces a generative HOI spatial rectification module to predict ray-depth corrections and rectify hand-object relative placement.<n>Last, a contact-aware joint optimization with dynamically updated contact constraints enforces geometric, temporal, and contact consistency.
• Score: 73.97421249653412
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We ask whether everyday open-world monocular videos can be turned into reusable 4D interaction primitives: articulated hand motion, object shape with 6D pose over time, and the when/where of contact. Such a capability would enable scalable mining of real interactions and, beyond reconstruction, support scene-aware synthesis and planning. However, reconstructing hand-object interaction (HOI) from challenging monocular videos remains difficult: methods often assume known objects or curated scenes, and separately estimated hands and objects easily become misaligned under clutter, occlusion, and unseen object geometries. Targeting this setting, we present CHOIR, a Contact-aware HOI Reconstruction framework for a monocular camera, using contact as an explicit coupling signal between hands and objects. CHOIR first initializes a coarse, contact-agnostic 4D HOI sequence from open-world visual priors. It then introduces a generative HOI spatial rectification module to predict ray-depth corrections and rectify hand-object relative placement, then derive initial per-frame contact correspondences on the rectified geometry. Last, a contact-aware joint optimization with dynamically updated contact constraints enforces geometric, temporal, and contact consistency. Experiments on controlled and challenging videos show that CHOIR improves object reconstruction, physical plausibility, and temporal consistency over state-of-the-art methods.

Related papers

• UnfoldArt: Zero-Shot Recovery of Full Articulated 3D Objects from Text or Image [58.40343808003224]
  We present a debate-driven approach to articulated 3D object reconstruction from text or image inputs.<n>High-level agents reason about object semantics and motion using knowledge from vision-language and video models.<n>Low-level agents estimate articulation parameters and interaction points.<n>The same video prior, conditioned on the agreed articulation, then drives each part through its motion to expose occluded interiors and geometry.
  arXiv  Detail & Related papers  (2026-06-29T17:44:53Z)
• You Only Touch Once: 6-DoF Object Pose Estimation from Single Tactile Contact [42.491016490387466]
  YOTO is a tactile-only pose estimation system that recovers the full 6-DoF object pose from a single pair of simultaneous contacts.<n>YOTO represents each tactile contact as a local 3D point cloud and localizes it on the object surface through a coarse-to-fine network.<n>Experiments on four geometrically diverse objects demonstrate accurate tactile contact localization and pose estimation, outperforming vision-based and geometric baselines.
  arXiv  Detail & Related papers  (2026-06-27T13:12:57Z)
• High-Fidelity 4D Hand-Object Capture via Multi-View Spatiotemporal Tracking and Physics-Aware Gaussians [38.0162622592412]
  We propose a novel system for the robust and accurate reconstruction of hands and objects from synchronized and calibrated multi-view videos.<n>Our pipeline achieves highly robust, artifact-free reconstruction, providing an efficient foundation for automated 4D asset generation.
  arXiv  Detail & Related papers  (2026-06-14T16:36:49Z)
• ArtHOI: Articulated Human-Object Interaction Synthesis by 4D Reconstruction from Video Priors [51.06020148149403]
  We introduce ArtHOI, the first zero-shot framework for articulated human-object interaction synthesis via 4D reconstruction from video priors.<n>ArtHOI bridges video-based generation and geometry-aware reconstruction, producing interactions that are both semantically aligned and physically grounded.
  arXiv  Detail & Related papers  (2026-03-04T17:58:04Z)
• ForeHOI: Feed-forward 3D Object Reconstruction from Daily Hand-Object Interaction Videos [22.436134664301473]
  We introduce ForeHOI, a novel feed-forward model that directly reconstructs 3D object geometry from monocular hand-object interaction videos.<n>ForeHOI achieves state-of-the-art performance in object reconstruction, significantly outperforming previous methods with around a 100x speedup.
  arXiv  Detail & Related papers  (2026-02-05T22:05:57Z)
• Object Reconstruction under Occlusion with Generative Priors and Contact-induced Constraints [20.702086497025494]
  In this paper, we leverage two extra sources of information to reduce the ambiguity of vision signals.<n>First, generative models learn priors of the shapes of commonly seen objects, allowing us to make reasonable guesses of the unseen part of geometry.<n>Second, contact information, which can be obtained from videos and physical interactions, provides sparse constraints on the boundary of the geometry.
  arXiv  Detail & Related papers  (2025-12-04T18:45:14Z)
• Dynamic Reconstruction of Hand-Object Interaction with Distributed Force-aware Contact Representation [47.940270914254285]
  ViTaM-D is a visual-tactile framework for reconstructing dynamic hand-object interaction with distributed tactile sensing.<n> DF-Field is a force-aware contact representation leveraging kinetic and potential energy in hand-object interactions.<n>ViTaM-D outperforms state-of-the-art methods in reconstruction accuracy for both rigid and deformable objects.
  arXiv  Detail & Related papers  (2024-11-14T16:29:45Z)
• HOLD: Category-agnostic 3D Reconstruction of Interacting Hands and Objects from Video [70.11702620562889]
  HOLD -- the first category-agnostic method that reconstructs an articulated hand and object jointly from a monocular interaction video. We develop a compositional articulated implicit model that can disentangled 3D hand and object from 2D images. Our method does not rely on 3D hand-object annotations while outperforming fully-supervised baselines in both in-the-lab and challenging in-the-wild settings.
  arXiv  Detail & Related papers  (2023-11-30T10:50:35Z)
• Learning Explicit Contact for Implicit Reconstruction of Hand-held Objects from Monocular Images [59.49985837246644]
  We show how to model contacts in an explicit way to benefit the implicit reconstruction of hand-held objects. In the first part, we propose a new subtask of directly estimating 3D hand-object contacts from a single image. In the second part, we introduce a novel method to diffuse estimated contact states from the hand mesh surface to nearby 3D space.
  arXiv  Detail & Related papers  (2023-05-31T17:59:26Z)
• HMDO: Markerless Multi-view Hand Manipulation Capture with Deformable Objects [8.711239906965893]
  HMDO is the first markerless deformable interaction dataset recording interactive motions of the hands and deformable objects. The proposed method can reconstruct interactive motions of hands and deformable objects with high quality.
  arXiv  Detail & Related papers  (2023-01-18T16:55:15Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.