Point Cloud Models
You Only Hypothesize Once
Introduced by Wang et al. in You Only Hypothesize Once: Point Cloud Registration with Rotation-equivariant DescriptorsYou Only Hypothesize Once is a local descriptor-based framework for the registration of two unaligned point clouds. The proposed descriptor achieves the rotation invariance by recent technologies of group equivariant feature learning, which brings more robustness to point density and noise. The descriptor in YOHO also has a rotation-equivariant part, which enables the estimation the registration from just one correspondence hypothesis.
Source: You Only Hypothesize Once: Point Cloud Registration with Rotation-equivariant Descriptors
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Retrieval | 2 | 20.00% |
| Sound Event Detection | 2 | 20.00% |
| Speech Recognition | 2 | 20.00% |
| Point Cloud Registration | 1 | 10.00% |
| Classification | 1 | 10.00% |
| Information Retrieval | 1 | 10.00% |
| Music Information Retrieval | 1 | 10.00% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
