3D-DefectBench

3D-DefectBench A controlled benchmark for evaluating vision-language models (VLMs) as fine-grained judges of defects in text-to-3D generation. 3D-DefectBench is a VLM-as-a-judge benchmark for detecting fine-grained defects in textured 3D meshes. It lets you measure how well any VLM judge aligns with human judgment: run your judge over the assets and score its predictions against the human defect labels provided here. Each example pairs a text prompt with a generated, textured 3D… See the full description on the dataset page:

Source: Hugging Face Hub (zzhao0500/3D-DefectBench). Metadata imported from the dataset’s Hub tags.