mlsanityData to 7 Oct 2026

Tetris3D: 3D Scene Generation With Objects That Fit Together

arXiv 2610.10539 ↗First posted 7 Oct 2026cs.CVcited by 0

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Abstract (arXiv)

We propose Tetris3D, a generative framework for single-image 3D scene reconstruction that recovers objects which are physically and geometrically coherent as a scene. Existing methods often generate objects independently or couple them implicitly, providing limited guidance for ensuring fine-grained spatial compatibility between neighboring objects that interact with one another. To address this, we explicitly condition the generation of each object on the geometry of surrounding objects and their physical relationships, guiding its shape and pose to remain geometrically and physically plausible within the scene. Moreover, we introduce ComOb, a physics simulation-based dataset of 1.2M scenes featuring physical interactions across diverse object categories, with per-object meshes and pairwise physical relation annotations. Comprehensive experiments on synthetic and realworld scenes show that Tetris3D recovers coherent object shapes and poses even when interacting regions are occluded, and achieves state-of-the-art performance in both generation quality and physical stability.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 22 of its 66 references that are in the map. First posted on arXiv 7 Oct 2026.

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22 of 66 references.

References · 22

  1. 2022Classifier-Free Diffusion Guidancecited by 5,717
  2. 2022Flow Matching for Generative Modelingcited by 5,426
  3. 2025Qwen3-VL Technical Reportcited by 2,534
  4. 2017Decoupled Weight Decay Regularizationcited by 1,722
  5. 2025DINOv3cited by 1,297
  6. 2022Point-E: A System for Generating 3D Point Clouds from Complex Promptscited by 694
  7. 2025Hunyuan3D 2.0: Scaling Diffusion Models for High Resolution Textured 3D Assets Generationcited by 342
  8. 2024Automated Creation of Digital Cousins for Robust Policy Learningcited by 88
  9. 2026ShapeR: Robust Conditional 3D Shape Generation from Casual Capturescited by 19
  10. 2025GENA3D: Generative Amodal 3D Modeling by Bridging 2D Priors and 3D Coherencecited by 4
  11. 2026Picasso: Holistic Scene Reconstruction with Physics-Constrained Samplingcited by 4
  12. 2026SimuScene: Simulation-Ready Compositional 3D Scene Reconstruction from a Single Imagecited by 4
10 more
  1. 2026PixARMesh: Autoregressive Mesh-Native Single-View Scene Reconstructioncited by 3
  2. 2026φ-Scene: Physically Grounded Image-to-3D Scene Reconstructioncited by 3
  3. 2026Axolotl3D: a Unified Framework for Faithful 3D Shape Completioncited by 2
  4. 2026WorldSculpt: Generating Compositional Worlds from Grounded Videoscited by 2
  5. 2026MessyKitchens: Contact-rich object-level 3D scene reconstructioncited by 1
  6. 2026SPREAD: Spatial-Physical REasoning via geometry Aware Diffusioncited by 1
  7. 2026Co-generation of Layout and Shape from Text via Autoregressive 3D Diffusioncited by 1
  8. 2026Pose-Aware Diffusion for 3D Generationcited by 1
  9. 2026PhyScene3D: Physically Consistent Interactive 3D Tabletop Scene Generationcited by 1
  10. 2026TableVerse: A Large-scale Tabletop Dataset with Real-world Grounded Layouts for Generalizable Manipulationcited by 1

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