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 1001–1010 of 2262 papers

Title	Date	Tasks	Status
Instance segmentation of buildings using keypoints	Jun 6, 2020	Instance SegmentationSegmentation	—Unverified
A Temporal Modeling Framework for Video Pre-Training on Video Instance Segmentation	Mar 22, 2025	Instance SegmentationSemantic Segmentation	—Unverified
Learning Vector Quantized Shape Code for Amodal Blastomere Instance Segmentation	Dec 2, 2020	Amodal Instance SegmentationInstance Segmentation	—Unverified
Instance segmentation of fallen trees in aerial color infrared imagery using active multi-contour evolution with fully convolutional network-based intensity priors	May 5, 2021	Instance SegmentationLine Segment Detection	—Unverified
Comparison of UNet, ENet, and BoxENet for Segmentation of Mast Cells in Scans of Histological Slices	Sep 15, 2019	Instance SegmentationSemantic Segmentation	—Unverified
Instance Segmentation of Industrial Point Cloud Data	Dec 24, 2020	Instance SegmentationSegmentation	—Unverified
Competitive Learning for Achieving Content-specific Filters in Video Coding for Machines	Jun 18, 2024	Instance Segmentationobject-detection	—Unverified
Advancing Oyster Phenotype Segmentation with Multi-Network Ensemble and Multi-Scale mechanism	Jan 20, 2025	Instance SegmentationSegmentation	—Unverified
Instance Segmentation of Reinforced Concrete Bridges with Synthetic Point Clouds	Sep 24, 2024	Instance SegmentationManagement	—Unverified
Grafting Vision Transformers	Oct 28, 2022	Image ClassificationInstance 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