File size: 3,085 Bytes
01d8ec5
 
 
 
 
 
 
 
 
 
 
 
 
 
 
0afed57
01d8ec5
 
 
27d5b54
01d8ec5
6a530ef
01d8ec5
 
 
27d5b54
 
6a530ef
01d8ec5
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
27d5b54
d4240ed
27d5b54
 
 
01d8ec5
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
---
license: cc-by-4.0
task_categories:
- text-to-3d
language:
- en
tags:
- benchmark
- evaluation
- multi-dimensional
- text-to-3d
- 3d-generation
pretty_name: T23D-CompBench
size_categories:
- 1K<n<10K
---

# Text-to-3D Comprehensive Benchmark (T23D-CompBench) 🎥📊

[Code](https://github.com/cbysjtu/rank2score_code) · [Project Page](https://cbysjtu.github.io/Rank2Score/) · [Paper@ArXiv](https://arxiv.org/abs/2509.23841) · [Prompt list](https://huggingface.co/datasets/ccccby/T23D-CompBench/blob/main/T23D-CompBench_prompt.json)

Welcome to the T23D-CompBench dataset! This repository contains around 3,600 textured meshes generated by various models using the [Prompt list](https://huggingface.co/datasets/ccccby/T23D-CompBench/blob/main/T23D-CompBench_prompt.json). These textured meshes have been annotated from twelve evaluation dimensions, including Object Alignment, Attribute Alignment, Interaction Alignment, Overall Alignment, Texture Clarity, Texture Aesthetics, Geometry Loss, Geometry Redundancy, Geometry Roughness, Overall Visual Quality, 3D Authentic, and Overall Quality.

## Dataset Details 📚

- **Paper:** [Read the Paper](https://arxiv.org/abs/2509.23841)
- **Code:** [Code](https://github.com/cbysjtu/rank2score_code) 
- **Prompt List (360 prompts):** [Prompt list](https://huggingface.co/datasets/ccccby/T23D-CompBench/blob/main/T23D-CompBench_prompt.json)
- **Project Page:** [Project Page](https://cbysjtu.github.io/Rank2Score/)
- **Models Included in T23D-CompBench dataset:**
  - [DreamFusion](https://github.com/threestudio-project/threestudio?tab=readme-ov-file)
  - [Magic3D](https://github.com/threestudio-project/threestudio?tab=readme-ov-file)
  - [3DTopia](https://github.com/3DTopia/3DTopia)
  - [Consistent3D](https://github.com/sail-sg/Consistent3D)
  - [One-2-3-45++](https://github.com/SUDO-AI-3D/One2345plus?tab=readme-ov-file)
  - [LGM](https://github.com/3DTopia/LGM)
  - [Hunyuan-2.0](https://github.com/Tencent-Hunyuan/Hunyuan3D-2)
  - [Meshy_AI-5](https://www.meshy.ai/)
  - [Rodin_Gen-1.5](https://hyper3d.ai/)
  - [Tripo_AI-2.5](https://www.tripo3d.ai/)
  
- **Dataset Structure:**
  Generate textured meshes are organized in the following structure (take 3DTopia for an example)
  ```
  ./3DTopia.zip/
  ├── A_asymmetrical_flower
    ├── model_normalized.obj
    ├── model_normalized.obj.mtl
    ├── material_0.png
  ├── A_bird_on_a_branch
    ├── model_normalized.obj
    ├── model_normalized.obj.mtl
    ├── material_0.png
  ...
  ```


## Acknowledgements and Citation 🙏

This dataset is based on the text-to-3D generative framework, which utilizes various open-source repositories for textured mesh generation evaluation. If you find this dataset helpful, please consider citing the original work:

```bash
@article{cui2025towards,
title={Towards Fine-Grained Text-to-3D Quality Assessment: A Database and A Two-Stage Rank-Learning Metric},
author={Bingyang Cui, Yujie Zhang, Qi Yang, Zhu Li, and Yiling Xu},
journal={arXiv preprint arXiv:2509.23841},
year={2025}
}
```