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 1071–1080 of 2262 papers

Title	Date	Tasks	Status
FSD V2: Improving Fully Sparse 3D Object Detection with Virtual Voxels	Aug 7, 2023	3D Multi-Object Tracking3D Object Detection	—Unverified
Assessing YOLACT++ for real time and robust instance segmentation of medical instruments in endoscopic procedures	Mar 30, 2021	Instance SegmentationReal-time Instance Segmentation	—Unverified
Fruit Detection, Segmentation and 3D Visualisation of Environments in Apple Orchards	Nov 28, 2019	Computational EfficiencyInstance Segmentation	—Unverified
Assessing SAM for Tree Crown Instance Segmentation from Drone Imagery	Mar 26, 2025	Instance SegmentationSemantic Segmentation	—Unverified
From Forks to Forceps: A New Framework for Instance Segmentation of Surgical Instruments	Nov 26, 2022	ARCClassification	—Unverified
A Dataset for Lane Instance Segmentation in Urban Environments	Jul 3, 2018	Autonomous VehiclesInstance Segmentation	—Unverified
3D-Aware Instance Segmentation and Tracking in Egocentric Videos	Aug 19, 2024	3D Object ReconstructionInstance Segmentation	—Unverified
LVIS Challenge Track Technical Report 1st Place Solution: Distribution Balanced and Boundary Refinement for Large Vocabulary Instance Segmentation	Nov 4, 2021	Instance SegmentationSegmentation	—Unverified
Split and Expand: An inference-time improvement for Weakly Supervised Cell Instance Segmentation	Jul 21, 2020	Bias DetectionInstance Segmentation	—Unverified
1st Place Winner of the 2024 Pixel-level Video Understanding in the Wild (CVPR'24 PVUW) Challenge in Video Panoptic Segmentation and Best Long Video Consistency of Video Semantic Segmentation	Jun 8, 2024	BenchmarkingInstance Segmentation	—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