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 | OneFormer (InternImage-H, emb_dim=1024, single-scale, 896x896, COCO-Pretrained) | AP | 44.2 | — | Unverified |
| 2 | Mask2Former (ResNet-50) | APL | 43.1 | — | Unverified |
| 3 | OpenSeeD | AP | 42.6 | — | Unverified |
| 4 | ViT-P (OneFormer, DiNAT-L, single-scale, 1280x1280, COCO_pretrain) | AP | 40.7 | — | Unverified |
| 5 | OneFormer (DiNAT-L, single-scale, 1280x1280, COCO-pretrain) | AP | 40.2 | — | Unverified |
| 6 | X-Decoder (Davit-d5, Deform, single-scale, 1280x1280) | AP | 38.7 | — | Unverified |
| 7 | ViT-P (OneFormer, DiNAT-L, single-scale, 1280x1280) | AP | 37.8 | — | Unverified |
| 8 | OneFormer (DiNAT-L, single-scale) | AP | 36 | — | Unverified |
| 9 | OneFormer (Swin-L, single-scale) | AP | 35.9 | — | Unverified |
| 10 | X-Decoder (L) | AP | 35.8 | — | Unverified |