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

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Showing 1331–1340 of 2262 papers

Title	Date	Tasks	Status
Practical Guidelines for Cell Segmentation Models Under Optical Aberrations in Microscopy	Apr 12, 2024	BenchmarkingCell Segmentation	—Unverified
Benchmarking the Robustness of Instance Segmentation Models	Sep 2, 2021	BenchmarkingDomain Adaptation	—Unverified
Bend-Net: Bending Loss Regularized Multitask Learning Network for Nuclei Segmentation in Histopathology Images	Sep 30, 2021	Instance SegmentationSegmentation	—Unverified
Better (pseudo-)labels for semi-supervised instance segmentation	Mar 18, 2024	Few-Shot Learningimage-classification	—Unverified
Beyond Appearance: Geometric Cues for Robust Video Instance Segmentation	Jul 8, 2025	Depth EstimationDepth Prediction	—Unverified
Beyond Grids: Learning Graph Representations for Visual Recognition	Dec 1, 2018	Instance Segmentationobject-detection	—Unverified
Beyond mAP: Towards better evaluation of instance segmentation	Jul 4, 2022	Instance SegmentationSegmentation	—Unverified
Beyond the Final Layer: Hierarchical Query Fusion Transformer with Agent-Interpolation Initialization for 3D Instance Segmentation	Feb 6, 2025	3D Instance SegmentationDecoder	—Unverified
BFS-Net: Weakly Supervised Cell Instance Segmentation from Bright-Field Microscopy Z-Stacks	Jun 9, 2022	Instance SegmentationSemantic Segmentation	—Unverified
Deep Multicameral Decoding for Localizing Unoccluded Object Instances from a Single RGB Image	Jun 18, 2019	Boundary DetectionDecoder	—Unverified

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All datasets COCO test-dev COCO minival LVIS v1.0 val Cityscapes val ADE20K val ARMBench Occluded COCO OoDIS Separated COCO TBBR BDD100K val COCO val (panoptic labels)

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	InternImage-H	AP50	80.8	—	Unverified
2	ResNeSt-200 (multi-scale)	AP50	70.2	—	Unverified
3	CenterMask + VoVNetV2-99 (multi-scale)	AP50	66.2	—	Unverified
4	CenterMask + VoVNetV2-57 (single-scale)	AP50	60.8	—	Unverified
5	Co-DETR	mask AP	57.1	—	Unverified
6	CBNetV2 (EVA02, single-scale)	mask AP	56.1	—	Unverified
7	ISDA (ResNet-50)	APL	55.7	—	Unverified
8	EVA	mask AP	55.5	—	Unverified
9	FD-SwinV2-G	mask AP	55.4	—	Unverified
10	Mask Frozen-DETR	mask AP	55.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	InternImage-B	GFLOPs	501	—	Unverified
2	Co-DETR	mask AP	56.6	—	Unverified
3	ViT-CoMer-L (Mask RCNN, DINOv2)	mask AP	55.9	—	Unverified
4	InternImage-H	mask AP	55.4	—	Unverified
5	EVA	mask AP	55	—	Unverified
6	Mask Frozen-DETR	mask AP	54.9	—	Unverified
7	MasK DINO (SwinL, multi-scale)	mask AP	54.5	—	Unverified
8	ViT-Adapter-L (HTC++, BEiTv2, O365, multi-scale)	mask AP	54.2	—	Unverified
9	GLEE-Pro	mask AP	54.2	—	Unverified
10	SwinV2-G (HTC++)	mask AP	53.7	—	Unverified