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 91–100 of 2262 papers

Title	Date	Tasks	Status	Hype
RMT: Retentive Networks Meet Vision Transformers	Sep 20, 2023	Instance Segmentationobject-detection	CodeCode Available	2
DAT++: Spatially Dynamic Vision Transformer with Deformable Attention	Sep 4, 2023	Image ClassificationInstance Segmentation	CodeCode Available	2
OpenIns3D: Snap and Lookup for 3D Open-vocabulary Instance Segmentation	Sep 1, 2023	3D Open-Vocabulary Instance Segmentation3D Open-Vocabulary Object Detection	CodeCode Available	2
DatasetDM: Synthesizing Data with Perception Annotations Using Diffusion Models	Aug 11, 2023	Dataset GenerationDecoder	CodeCode Available	2
RSPrompter: Learning to Prompt for Remote Sensing Instance Segmentation based on Visual Foundation Model	Jun 28, 2023	Image SegmentationInstance Segmentation	CodeCode Available	2
CellViT: Vision Transformers for Precise Cell Segmentation and Classification	Jun 27, 2023	Cell DetectionCell Segmentation	CodeCode Available	2
OpenMask3D: Open-Vocabulary 3D Instance Segmentation	Jun 23, 2023	3D Instance Segmentation3D Open-Vocabulary Instance Segmentation	CodeCode Available	2
Does Image Anonymization Impact Computer Vision Training?	Jun 8, 2023	Face AnonymizationInstance Segmentation	CodeCode Available	2
SAMRS: Scaling-up Remote Sensing Segmentation Dataset with Segment Anything Model	May 3, 2023	Instance SegmentationObject	CodeCode Available	2
RegionPLC: Regional Point-Language Contrastive Learning for Open-World 3D Scene Understanding	Apr 3, 2023	Contrastive LearningInstance Segmentation	CodeCode Available	2

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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	GLEE-Pro	mask AP	54.2	—	Unverified
9	ViT-Adapter-L (HTC++, BEiTv2, O365, multi-scale)	mask AP	54.2	—	Unverified
10	SwinV2-G (HTC++)	mask AP	53.7	—	Unverified