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 1421–1430 of 2262 papers

Title	Date	Tasks	Status
Continental-Scale Building Detection from High Resolution Satellite Imagery	Jul 26, 2021	Instance SegmentationSemantic Segmentation	—Unverified
Contour Loss for Instance Segmentation via k-step Distance Transformation Image	Feb 22, 2021	Instance SegmentationSegmentation	—Unverified
ContourRender: Detecting Arbitrary Contour Shape For Instance Segmentation In One Pass	Jun 7, 2021	Instance SegmentationSemantic Segmentation	—Unverified
Contrastive Learning for Automotive mmWave Radar Detection Points Based Instance Segmentation	Mar 13, 2022	Autonomous DrivingContrastive Learning	—Unverified
Convolutional Neural Networks based automated segmentation and labelling of the lumbar spine X-ray	Apr 4, 2020	Instance SegmentationSegmentation	—Unverified
Copy-Paste Image Augmentation with Poisson Image Editing for Ultrasound Instance Segmentation Learning	Aug 28, 2023	DiversityImage Augmentation	—Unverified
CORP: A Multi-Modal Dataset for Campus-Oriented Roadside Perception Tasks	Apr 4, 2024	Autonomous DrivingInstance Segmentation	—Unverified
AdaCoSeg: Adaptive Shape Co-Segmentation with Group Consistency Loss	Mar 25, 2019	Instance SegmentationSegmentation	—Unverified
Could Giant Pretrained Image Models Extract Universal Representations?	Nov 3, 2022	Action RecognitionAction Recognition In Videos	—Unverified
Counting and Segmenting Sorghum Heads	May 30, 2019	Crowd CountingInstance 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