4D Panoptic Segmentation
4D Panoptic Segmentation is a computer vision task that extends video panoptic segmentation to point cloud sequences. That is, given a point cloud sequence, the goal is to predict the semantic class of each point while consistently tracking object instances. Here, the points belonging to the same object instance should be assigned the same instance ID throughout the point cloud sequence. LSTQ metric is used to evaluate the performance of this task. Video credit: Mask4Former
Papers
Showing 1–9 of 9 papers
Benchmark Results
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | Mask4Former | LSTQ | 68.4 | — | Unverified |
| 2 | Eq-4D-StOP | LSTQ | 67.8 | — | Unverified |
| 3 | Mask4D | LSTQ | 64.3 | — | Unverified |
| 4 | 4D-StOP | LSTQ | 63.9 | — | Unverified |
| 5 | CIA | LSTQ | 63.1 | — | Unverified |
| 6 | 4D-DS-Net | LSTQ | 62.3 | — | Unverified |
| 7 | 4D-PLS | LSTQ | 56.9 | — | Unverified |