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 561–570 of 2262 papers

Title	Date	Tasks	Status	Hype
Improving Mask R-CNN for Nuclei Instance Segmentation in Hematoxylin & Eosin-Stained Histological Images	Jul 20, 2021	Instance SegmentationSegmentation	CodeCode Available	1
Dynamic Convolution for 3D Point Cloud Instance Segmentation	Jul 18, 2021	Instance SegmentationSemantic Segmentation	CodeCode Available	1
Deep Learning based Food Instance Segmentation using Synthetic Data	Jul 15, 2021	Deep LearningInstance Segmentation	CodeCode Available	1
Visual Parser: Representing Part-whole Hierarchies with Transformers	Jul 13, 2021	DecoderImage Classification	CodeCode Available	1
NucMM Dataset: 3D Neuronal Nuclei Instance Segmentation at Sub-Cubic Millimeter Scale	Jul 13, 2021	Instance SegmentationRepresentation Learning	CodeCode Available	1
Locally Enhanced Self-Attention: Combining Self-Attention and Convolution as Local and Context Terms	Jul 12, 2021	Instance Segmentationobject-detection	CodeCode Available	1
Capturing, Reconstructing, and Simulating: the UrbanScene3D Dataset	Jul 9, 2021	3D ReconstructionInstance Segmentation	CodeCode Available	1
On Model Calibration for Long-Tailed Object Detection and Instance Segmentation	Jul 5, 2021	Instance SegmentationLong-tailed Object Detection	CodeCode Available	1
CBNet: A Composite Backbone Network Architecture for Object Detection	Jul 1, 2021	Instance SegmentationObject	CodeCode Available	1
Focal Self-attention for Local-Global Interactions in Vision Transformers	Jul 1, 2021	image-classificationImage Classification	CodeCode Available	1

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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