THU-LYJ-Lab/T3Bench resource

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

1098 stars · 11 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

T3Bench is the first comprehensive benchmark for text-to-3D generation, providing 300 text prompts across three complexity levels plus automatic quality and text-alignment metrics based on multi-view images and LLM evaluation. It includes evaluation pipelines built on ThreeStudio for testing methods like ProlificDreamer, Magic3D, Latent-NeRF, Fantasia3D, DreamFusion, and SJC.

Use cases

• benchmark text-to-3d generation models
• evaluate quality of 3d assets generated from text prompts
• measure text-3d alignment automatically
• compare latentnerf magic3d fantasia3d dreamfusion sjc prolificdreamer
• download precomputed mesh results for text-to-3d methods
• research on diffusion-guided nerf generation

When to choose

• you need standardized prompts and metrics to evaluate a text-to-3d method
• you want reproducible comparisons against published text-to-3d baselines
• you are researching multi-view consistency or text-3D alignment scoring

When to avoid

• you need a text-to-3d generator rather than an evaluation benchmark
• you want a maintained production tool - the project has no license and limited updates
• your 3D generation method is not supported by the ThreeStudio-based pipeline

Facets

dataset · maturity maintenance

benchmarking machine-learning artificial-intelligence computer-vision graphics machine-learning python text-to-3d 3d-generation diffusion-models nerf benchmark evaluation-metrics prompt-dataset llm-evaluation evaluation gpu linux

Member repositories

For agents

markdown · JSON · MCP: product_card(name="THU-LYJ-Lab/T3Bench")