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 1501–1510 of 2262 papers

Title	Date	Tasks	Status	Hype
Embedded Vision for Self-Driving on Forest Roads	May 27, 2021	GPUInstance Segmentation	—Unverified	0
ICDAR 2021 Competition on Historical Map Segmentation	May 27, 2021	Contour DetectionDocument Layout Analysis	CodeCode Available	0
BoundarySqueeze: Image Segmentation as Boundary Squeezing	May 25, 2021	Image SegmentationInstance Segmentation	CodeCode Available	1
Reinforcement learning for instance segmentation with high-level priors	May 21, 2021	graph partitioningInstance Segmentation	—Unverified	0
Deep Active Contours Using Locally Controlled Distance Vector Flow	May 18, 2021	Image SegmentationInstance Segmentation	—Unverified	0
Temporal Prediction and Evaluation of Brassica Growth in the Field using Conditional Generative Adversarial Networks	May 17, 2021	Instance SegmentationSemantic Segmentation	—Unverified	0
Instance Segmentation of Microscopic Foraminifera	May 15, 2021	Instance SegmentationNovel Object Detection	CodeCode Available	0
DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision	May 13, 2021	Box-supervised Instance SegmentationInstance Segmentation	CodeCode Available	1
Waste detection in Pomerania: non-profit project for detecting waste in environment	May 12, 2021	ClassificationInstance Segmentation	CodeCode Available	1
Incremental Few-Shot Instance Segmentation	May 11, 2021	Few-shot Instance SegmentationInstance Segmentation	CodeCode Available	1

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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