qizekun/3D-MM-Vet

3D MM-Vet

3D MM-Vet is a carefully crafted multi-level 3D QA benchmark that consists of 59 unique 3D models and 232 human-written questions and answers with rich content.

The test data and scripts have been uploaded to Hugging Face. You can also locate the evaluation scripts from the codebase of ShapeLLM.

Furthermore, we propose 3D MM-Vet-C, which contains three variants: single-view, jitter, and rotation. They represent extracting partial point clouds of the front view field of view, adding Gaussian noise to the point cloud xyz, and random rotation on the x, y, and z axes, respectively.

Here is a more detailed explanation of each variant:

• Single-view: This variant focuses on the model's ability to understand the 3D object from a single viewpoint. To create the single-view variant, we extract the front-view point cloud of each model.
• Jitter: This variant tests the model's robustness to noise. To create the jitter variant, we add Gaussian noise with zero mean and variance of 0.01 to the point cloud xyz.
• Rotation: This variant examines the model's ability to understand the 3D scene from different viewpoints. To create the rotation variant, we randomly apply 30 degrees of random rotation on the x, y, and z axes.

We believe that 3D MM-Vet and 3D MM-Vet-C are valuable resources for the 3D QA community. They can be used to evaluate the performance of existing models and to develop new models that are better at understanding and reasoning about 3D objects.