# TexVerse: A Universe of 3D Objects with High-Resolution Textures

arXiv: https://arxiv.org/abs/2508.10868 · HTML: https://mlsanity.com/paper/2508.10868/

## Key facts

- Cited by 45 papers in the map (data through 14 Oct 2026).
- Builds on 18 of its 18 references that are in the map.
- First posted on arXiv 14 Aug 2025.

## Builds on (most cited first, 18 of 18)

- [ShapeNet: An Information-Rich 3D Model Repository](https://mlsanity.com/paper/1512.03012/) (2015)
- [Objaverse: A Universe of Annotated 3D Objects](https://mlsanity.com/paper/2212.08051/) (2022)
- [Objaverse-XL: A Universe of 10M+ 3D Objects](https://mlsanity.com/paper/2307.05663/) (2023)
- [Google Scanned Objects: A High-Quality Dataset of 3D Scanned Household Items](https://mlsanity.com/paper/2204.11918/) (2022)
- [CLAY: A Controllable Large-scale Generative Model for Creating High-quality 3D Assets](https://mlsanity.com/paper/2406.13897/) (2024)
- [ABO: Dataset and Benchmarks for Real-World 3D Object Understanding](https://mlsanity.com/paper/2110.06199/) (2021)
- [Hunyuan3D 2.0: Scaling Diffusion Models for High Resolution Textured 3D Assets Generation](https://mlsanity.com/paper/2501.12202/) (2025)
- [OmniObject3D: Large-Vocabulary 3D Object Dataset for Realistic Perception, Reconstruction and Generation](https://mlsanity.com/paper/2301.07525/) (2023)
- [3D-FUTURE: 3D Furniture shape with TextURE](https://mlsanity.com/paper/2009.09633/) (2020)
- [Unique3D: High-Quality and Efficient 3D Mesh Generation from a Single Image](https://mlsanity.com/paper/2405.20343/) (2024)
- [Hunyuan3D 2.5: Towards High-Fidelity 3D Assets Generation with Ultimate Details](https://mlsanity.com/paper/2506.16504/) (2025)
- [Direct3D-S2: Gigascale 3D Generation Made Easy with Spatial Sparse Attention](https://mlsanity.com/paper/2505.17412/) (2025)
- [Sparc3D: Sparse Representation and Construction for High-Resolution 3D Shapes Modeling](https://mlsanity.com/paper/2505.14521/) (2025)
- [SparseFlex: High-Resolution and Arbitrary-Topology 3D Shape Modeling](https://mlsanity.com/paper/2503.21732/) (2025)
- [Ultra3D: Efficient and High-Fidelity 3D Generation with Part Attention](https://mlsanity.com/paper/2507.17745/) (2025)
- [MVPaint: Synchronized Multi-View Diffusion for Painting Anything 3D](https://mlsanity.com/paper/2411.02336/) (2024)
- [Digital Twin Catalog: A Large-Scale Photorealistic 3D Object Digital Twin Dataset](https://mlsanity.com/paper/2504.08541/) (2025)
- [GT23D-Bench: A Comprehensive General Text-to-3D Generation Benchmark](https://mlsanity.com/paper/2412.09997/) (2024)

## Built on by (most cited first, 30 of 45)

- [Native and Compact Structured Latents for 3D Generation](https://mlsanity.com/paper/2512.14692/) (2025)
- [LingBot-Map: Geometric Context Transformer for Streaming 3D Reconstruction](https://mlsanity.com/paper/2604.14141/) (2026)
- [MolmoPoint: Better Pointing for VLMs with Grounding Tokens](https://mlsanity.com/paper/2603.28069/) (2026)
- [AutoUE: Automated Generation of 3D Games in Unreal Engine via Multi-Agent Systems](https://mlsanity.com/paper/2603.07106/) (2026)
- [SplatPainter: Interactive Authoring of 3D Gaussians from 2D Edits via Test-Time Training](https://mlsanity.com/paper/2512.05354/) (2025)
- [Engine-Native Editable 3D World Reconstruction with Objects and Lighting](https://mlsanity.com/paper/2607.20889/) (2026)
- [OLATverse: A Large-scale Real-world Object Dataset with Precise Lighting Control](https://mlsanity.com/paper/2511.02483/) (2025)
- [LaFiTe: A Generative Latent Field for 3D Native Texturing](https://mlsanity.com/paper/2512.04786/) (2025)
- [MeshTailor: Cutting Seams via Generative Mesh Traversal](https://mlsanity.com/paper/2603.27309/) (2026)
- [Artiverse: A Diverse and Physically Grounded Dataset for Articulated Objects](https://mlsanity.com/paper/2605.24403/) (2026)
- [Name That Part: 3D Part Segmentation and Naming](https://mlsanity.com/paper/2512.18003/) (2025)
- [EVA01: Unified Native 3D Understanding and Generation via Mixture-of-Transformers](https://mlsanity.com/paper/2605.16745/) (2026)
- [Sat2City v2: Native 3D City Asset Generation from a Single Satellite Image](https://mlsanity.com/paper/2606.24138/) (2026)
- [NI-Tex: Non-isometric Image-based Garment Texture Generation](https://mlsanity.com/paper/2511.18765/) (2025)
- [Know3D: Prompting 3D Generation with Knowledge from Vision-Language Models](https://mlsanity.com/paper/2603.22782/) (2026)
- [Camera Control for Text-to-Image Generation via Learning Viewpoint Tokens](https://mlsanity.com/paper/2604.19954/) (2026)
- [Droplet3D: Commonsense Priors from Videos Facilitate 3D Generation](https://mlsanity.com/paper/2508.20470/) (2025)
- [SPRig: Self-Supervised Pose-Invariant Rigging from Mesh Sequences](https://mlsanity.com/paper/2602.12740/) (2026)
- [Helix4D: Complex 4D Mesh Generation](https://mlsanity.com/paper/2605.26109/) (2026)
- [AnySurf: Any Surface Generation with Directed Edge](https://mlsanity.com/paper/2605.26149/) (2026)
- [MeshLoom: Feed-Forward Non-Rigid Registration of Mesh Sequences](https://mlsanity.com/paper/2606.17027/) (2026)
- [Mesh BDF: Barycentric Dominance Field for 3D Native Mesh Generation](https://mlsanity.com/paper/2606.31777/) (2026)
- [Ink3D: Sculpting 3D Assets with Extremely Complex Textures via Video Generative Models](https://mlsanity.com/paper/2607.01222/) (2026)
- [EditVerse3D: High-Quality 3D Object Editing with Region-Aware Learning](https://mlsanity.com/paper/2607.07187/) (2026)
- [TexSpot: 3D Texture Enhancement with Spatially-uniform Point Latent Representation](https://mlsanity.com/paper/2602.12157/) (2026)
- [Material Magic Wand: Material-Aware Grouping of 3D Parts in Untextured Meshes](https://mlsanity.com/paper/2603.17370/) (2026)
- [GO-Renderer: Generative Object Rendering with 3D-aware Controllable Video Diffusion Models](https://mlsanity.com/paper/2603.23246/) (2026)
- [H-OmniStereo: Zero-Shot Omnidirectional Stereo Matching with Heading-Aligned Normal Priors](https://mlsanity.com/paper/2605.14963/) (2026)
- [SpatialBench: Is Your Spatial Foundation Model an All-Round Player?](https://mlsanity.com/paper/2605.27367/) (2026)
- [Every9D-21M: Large-Scale Real-World 9D Canonicalization of Everyday Objects](https://mlsanity.com/paper/2605.28270/) (2026)

## Abstract (arXiv)

We introduce TexVerse, a large-scale 3D dataset featuring high-resolution textures. While recent advances in large-scale 3D datasets have enhanced high-resolution geometry generation, creating high-resolution textures end-to-end remains underexplored due to the lack of suitable datasets. TexVerse fills this gap with a curated collection of over 858K unique high-resolution 3D models sourced from Sketchfab, including more than 158K models with physically based rendering (PBR) materials. Each model encompasses all of its high-resolution variants, bringing the total to 1.6M 3D instances. TexVerse also includes specialized subsets: TexVerse-Skeleton, with 69K rigged models, and TexVerse-Animation, with 54K animated models, both preserving original skeleton and animation data uploaded by the user. We also provide detailed model annotations describing overall characteristics, structural components, and intricate features. TexVerse offers a high-quality data resource with wide-ranging potential applications in texture synthesis, PBR material development, animation, and various 3D vision and graphics tasks.