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 1031–1040 of 2262 papers

Title	Date	Tasks	Status
Gland Instance Segmentation by Deep Multichannel Neural Networks	Jul 17, 2016	Instance SegmentationSegmentation	—Unverified
Gland Instance Segmentation by Deep Multichannel Side Supervision	Jul 12, 2016	Instance SegmentationSegmentation	—Unverified
GIN: Generative INvariant Shape Prior for Amodal Instance Segmentation	Sep 22, 2023	Amodal Instance SegmentationInstance Segmentation	—Unverified
Combining Datasets with Different Label Sets for Improved Nucleus Segmentation and Classification	Oct 5, 2023	Instance SegmentationSegmentation	—Unverified
Geomorphological Analysis Using Unpiloted Aircraft Systems, Structure from Motion, and Deep Learning	Sep 27, 2019	Instance SegmentationMorphological Analysis	—Unverified
Color Space-based HoVer-Net for Nuclei Instance Segmentation and Classification	Mar 3, 2022	Instance SegmentationSegmentation	—Unverified
ColorRL: Reinforced Coloring for End-to-End Instance Segmentation	Jun 19, 2021	Deep Reinforcement LearningInstance Segmentation	—Unverified
Geometry-Aware Fruit Grasping Estimation for Robotic Harvesting in Orchards	Dec 8, 2021	Instance SegmentationSemantic Segmentation	—Unverified
Geometric Image Synthesis	Sep 12, 2018	Image GenerationInstance Segmentation	—Unverified
A Survey on Cell Nuclei Instance Segmentation and Classification: Leveraging Context and Attention	Jul 26, 2024	ClassificationInstance Segmentation	—Unverified

Show:10 25 50

← PrevPage 104 of 227Next →

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