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 971–980 of 2262 papers

Title	Date	Tasks	Status	Hype
From Forks to Forceps: A New Framework for Instance Segmentation of Surgical Instruments	Nov 26, 2022	ARCClassification	—Unverified	0
EasyMLServe: Easy Deployment of REST Machine Learning Services	Nov 26, 2022	Instance SegmentationSemantic Segmentation	CodeCode Available	0
Automating Cobb Angle Measurement for Adolescent Idiopathic Scoliosis using Instance Segmentation	Nov 25, 2022	Instance SegmentationSemantic Segmentation	—Unverified	0
Language-Assisted 3D Feature Learning for Semantic Scene Understanding	Nov 25, 2022	DescriptiveInstance Segmentation	CodeCode Available	1
A Benchmark of Long-tailed Instance Segmentation with Noisy Labels	Nov 24, 2022	Instance SegmentationSegmentation	CodeCode Available	0
How do Cross-View and Cross-Modal Alignment Affect Representations in Contrastive Learning?	Nov 23, 2022	Contrastive Learningcross-modal alignment	—Unverified	0
EurNet: Efficient Multi-Range Relational Modeling of Spatial Multi-Relational Data	Nov 23, 2022	image-classificationImage Classification	CodeCode Available	0
Rethinking Implicit Neural Representations for Vision Learners	Nov 22, 2022	image-classificationImage Classification	—Unverified	0
DETRs with Collaborative Hybrid Assignments Training	Nov 22, 2022	DecoderInstance Segmentation	CodeCode Available	3
Task-Specific Data Augmentation and Inference Processing for VIPriors Instance Segmentation Challenge	Nov 21, 2022	Autonomous DrivingData Augmentation	—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