| Paper | Code | Accuracy (%) | Parameters | Need 3D Data? | ModelName | ReleaseDate |
|---|---|---|---|---|---|---|
| Point-GN: A Non-Parametric Network Using Gaussian Positional Encoding for Point Cloud Classification | ✓ Link | 85.3 | 0M | Yes | Point-GN | 2024-12-04 |
| Parameter is Not All You Need: Starting from Non-Parametric Networks for 3D Point Cloud Analysis | ✓ Link | 82.6 | 0M | Yes | Point-NN | 2023-03-14 |
| PointCLIP V2: Prompting CLIP and GPT for Powerful 3D Open-world Learning | ✓ Link | 64.2 | No | PointCLIP V2 | 2022-11-21 | |
| ULIP: Learning a Unified Representation of Language, Images, and Point Clouds for 3D Understanding | ✓ Link | 60.4 | Yes | ULIP | 2022-12-10 | |
| CLIP2Point: Transfer CLIP to Point Cloud Classification with Image-Depth Pre-training | ✓ Link | 49.4 | Yes | CLIP2Point | 2022-10-03 | |
| CALIP: Zero-Shot Enhancement of CLIP with Parameter-free Attention | ✓ Link | 21.5 | No | CALIP | 2022-09-28 | |
| PointCLIP: Point Cloud Understanding by CLIP | ✓ Link | 20.2 | No | PointCLIP | 2021-12-04 |