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-T (ImageNet-1k pretrain) | Average Recall@IoU:0.5-0.95 | 28 | — | Unverified |
| 2 | Mask R-CNN (ResNet-50-FPN, ImageNet-1k pretrain) | Average Recall@IoU:0.5-0.95 | 21.9 | — | Unverified |
| 3 | Swin-T | Average Recall@IoU:0.5-0.95 | 20.6 | — | Unverified |
| 4 | Mask R-CNN (ResNet-50-FPN) | Average Recall@IoU:0.5-0.95 | 20.1 | — | Unverified |
| 5 | Wahn Mask R-CNN | Average Recall@IoU:0.5-0.95 | 9.4 | — | Unverified |