Instance Segmentation
Instance Segmentation is a computer vision task that involves identifying and separating individual objects within an image, including detecting the boundaries of each object and assigning a unique label to each object. The goal of instance segmentation is to produce a pixel-wise segmentation map of the image, where each pixel is assigned to a specific object instance.
Image Credit: Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers, CVPR'21
Papers
Showing 1–10 of 2262 papers
All datasetsCOCO test-devCOCO minivalLVIS v1.0 valCityscapes valADE20K valARMBenchOccluded COCOOoDISSeparated COCOTBBRBDD100K valCOCO val (panoptic labels)
Benchmark Results
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | Swin-B + Cascade Mask R-CNN (tri-layer modelling) | Mean Recall | 63.64 | — | Unverified |
| 2 | Swin-B + Cascade Mask R-CNN | Mean Recall | 62.9 | — | Unverified |
| 3 | Swin-S + Mask R-CNN (tri-layer plugin) | Mean Recall | 62.58 | — | Unverified |
| 4 | Swin-T + Mask R-CNN (tri-layer plugin) | Mean Recall | 62 | — | Unverified |
| 5 | Swin-S + Mask R-CNN | Mean Recall | 61.14 | — | Unverified |
| 6 | Swin-T + Mask R-CNN | Mean Recall | 58.81 | — | Unverified |