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 671–680 of 2262 papers

Title	Date	Tasks	Status	Hype
FoodSAM: Any Food Segmentation	Aug 11, 2023	Image SegmentationInstance Segmentation	CodeCode Available	1
Fine-grained building roof instance segmentation based on domain adapted pretraining and composite dual-backbone	Aug 10, 2023	Data AugmentationDiversity	—Unverified	0
Pseudo-label Alignment for Semi-supervised Instance Segmentation	Aug 10, 2023	Instance SegmentationPseudo Label	CodeCode Available	1
Instance segmentation based 6D pose estimation of industrial objects using point clouds for robotic bin-picking	Aug 10, 2023	6D Pose EstimationInstance Segmentation	—Unverified	0
A Unified Interactive Model Evaluation for Classification, Object Detection, and Instance Segmentation in Computer Vision	Aug 9, 2023	Instance Segmentationobject-detection	—Unverified	0
Deep Learning for Morphological Identification of Extended Radio Galaxies using Weak Labels	Aug 9, 2023	Instance SegmentationPathfinder	CodeCode Available	0
1st Place Solution for CVPR2023 BURST Long Tail and Open World Challenges	Aug 8, 2023	Instance SegmentationSemantic Segmentation	—Unverified	0
Exploring Transformers for Open-world Instance Segmentation	Aug 8, 2023	Contrastive LearningInstance Segmentation	—Unverified	0
FSD V2: Improving Fully Sparse 3D Object Detection with Virtual Voxels	Aug 7, 2023	3D Multi-Object Tracking3D Object Detection	—Unverified	0
Mask Frozen-DETR: High Quality Instance Segmentation with One GPU	Aug 7, 2023	GPUInstance 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