mlsanityData to 7 Oct 2026

HY3D-Bench: Generation of 3D Assets

arXiv 2602.03907 ↗First posted 3 Feb 2026cs.CV cs.AIcited by 11

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Abstract (arXiv)

While recent advances in neural representations and generative models have revolutionized 3D content creation, the field remains constrained by significant data processing bottlenecks. To address this, we introduce HY3D-Bench, an open-source ecosystem designed to establish a unified, high-quality foundation for 3D generation. Our contributions are threefold: (1) We curate a library of 250k high-fidelity 3D objects distilled from large-scale repositories, employing a rigorous pipeline to deliver training-ready artifacts, including watertight meshes and multi-view renderings; (2) We introduce structured part-level decomposition, providing the granularity essential for fine-grained perception and controllable editing; and (3) We bridge real-world distribution gaps via a scalable AIGC synthesis pipeline, contributing 125k synthetic assets to enhance diversity in long-tail categories. Validated empirically through the training of Hunyuan3D-2.1-Small, HY3D-Bench democratizes access to robust data resources, aiming to catalyze innovation across 3D perception, robotics, and digital content creation.

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). Builds on 97 of its 106 references that are in the map. First posted on arXiv 3 Feb 2026.

Builds on

97 of 106 references.

References · 97

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38 more
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50 most cited of 97 All 97 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 11.

11 papers.

  1. 2026GeoPT: Scaling Physics Simulation via Lifted Geometric Pre-Trainingcited by 8
  2. 2026ArtLLM: Generating Articulated Assets via 3D LLMcited by 8
  3. 2026Feedforward 3D Editing Learns from Semantic-Part Transformationcited by 7
  4. 2026Omni123: Exploring 3D Native Foundation Models with Limited 3D Data by Unifying Text to 2D and 3D Generationcited by 3
  5. 2026Instruct-Particulate: Scaling Feed-Forward 3D Object Articulation with Kinematic Controlcited by 2
  6. 2026Know3D: Prompting 3D Generation with Knowledge from Vision-Language Modelscited by 1
  7. 2026Pose-Aware Diffusion for 3D Generationcited by 1
  8. 2026PartLLM: A Unified Multimodal Foundation for 3D Part Segmentationcited by 1
  9. 2026CompoSE: Compositional Synthesis and Editing of 3D Shapes via Part-Aware Controlcited by 0
  10. 2026HAT-4D: Lifting Monocular Video for 4D Multi-Object Interactions via Human-Agent Collaborationcited by 0
  11. 2026Global Pose Control for Generative View Synthesis in Normalized Object Coordinate Spacecited by 0