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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1691–1700 of 2262 papers

Title	Date	Tasks	Status	Hype
Panoster: End-to-end Panoptic Segmentation of LiDAR Point Clouds	Oct 28, 2020	ClusteringInstance Segmentation	—Unverified	0
Perception for Autonomous Systems (PAZ)	Oct 27, 2020	2D Object Detection6D Pose Estimation	CodeCode Available	1
Instance Semantic Segmentation Benefits from Generative Adversarial Networks	Oct 26, 2020	Autonomous DrivingInstance Segmentation	CodeCode Available	1
Detection and Segmentation of Lesion Areas in Chest CT Scans For The Prediction of COVID-19	Oct 26, 2020	COVID-19 DiagnosisCOVID-19 Image Segmentation	CodeCode Available	1
Amodal Segmentation through Out-of-Task and Out-of-Distribution Generalization with a Bayesian Model	Oct 25, 2020	Amodal Instance SegmentationInstance Segmentation	CodeCode Available	1
2nd Place Solution to Instance Segmentation of IJCAI 3D AI Challenge 2020	Oct 21, 2020	Instance SegmentationObject	—Unverified	0
AutoBSS: An Efficient Algorithm for Block Stacking Style Search	Oct 20, 2020	AutoMLBayesian Optimization	—Unverified	0
TTPLA: An Aerial-Image Dataset for Detection and Segmentation of Transmission Towers and Power Lines	Oct 20, 2020	Instance Segmentationobject-detection	CodeCode Available	1
Multi-Stage Fusion for One-Click Segmentation	Oct 19, 2020	Instance SegmentationInteractive Segmentation	—Unverified	0
Localized Interactive Instance Segmentation	Oct 18, 2020	Instance SegmentationInteractive Segmentation	—Unverified	0

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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