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 2041–2050 of 2262 papers

Title	Date	Tasks	Status
Segmentation of Multiple Myeloma Plasma Cells in Microscopy Images with Noisy Labels	Nov 8, 2021	Image AugmentationInstance Segmentation	—Unverified
Segmentation of the veterinary cytological images for fast neoplastic tumors diagnosis	May 7, 2023	Instance SegmentationSemantic Segmentation	—Unverified
Segment-Fusion: Hierarchical Context Fusion for Robust 3D Semantic Segmentation	Jan 1, 2022	3D Semantic SegmentationAutonomous Driving	—Unverified
Segmenting objects with Bayesian fusion of active contour models and convnet priors	Oct 9, 2024	Instance SegmentationSemantic Segmentation	—Unverified
Self-Prediction for Joint Instance and Semantic Segmentation of Point Clouds	Jul 27, 2020	Instance SegmentationPrediction	—Unverified
Self-Supervised Image Representation Learning with Geometric Set Consistency	Mar 29, 2022	Contrastive LearningInstance Segmentation	—Unverified
Self-Supervised Instance Segmentation by Grasping	May 10, 2023	Instance SegmentationRobotic Grasping	—Unverified
Self-Supervised Interactive Object Segmentation Through a Singulation-and-Grasping Approach	Jul 19, 2022	Instance SegmentationInteractive Segmentation	—Unverified
Self-supervised learning for autonomous vehicles perception: A conciliation between analytical and learning methods	Oct 3, 2019	Autonomous DrivingAutonomous Vehicles	—Unverified
Self-Supervised Learning for Robotic Leaf Manipulation: A Hybrid Geometric-Neural Approach	May 6, 2025	3D Depth EstimationDepth Estimation	—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