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 1776–1800 of 2262 papers

Title	Date	Tasks	Status
Instance segmentation with the number of clusters incorporated in embedding learning	Mar 27, 2021	ClusteringImage Segmentation	—Unverified
Weakly Supervised Instance Segmentation for Videos with Temporal Mask Consistency	Mar 23, 2021	Instance SegmentationRelation Network	—Unverified
Dilated SpineNet for Semantic Segmentation	Mar 23, 2021	Instance SegmentationSegmentation	—Unverified
Human De-occlusion: Invisible Perception and Recovery for Humans	Mar 22, 2021	Human ParsingInstance Segmentation	—Unverified
Generic Perceptual Loss for Modeling Structured Output Dependencies	Mar 18, 2021	Depth EstimationImage Generation	—Unverified
Robust 2D/3D Vehicle Parsing in CVIS	Mar 11, 2021	BenchmarkingData Augmentation	—Unverified
Instance Segmentation GNNs for One-Shot Conformal Tracking at the LHC	Mar 11, 2021	3D Instance SegmentationInstance Segmentation	—Unverified
Panoptic Lintention Network: Towards Efficient Navigational Perception for the Visually Impaired	Mar 6, 2021	Instance SegmentationPanoptic Segmentation	CodeCode Available
SCD: A Stacked Carton Dataset for Detection and Segmentation	Feb 25, 2021	Instance SegmentationSemantic Segmentation	CodeCode Available
SALT: A Semi-automatic Labeling Tool for RGB-D Video Sequences	Feb 22, 2021	Instance SegmentationSegmentation	—Unverified
Contour Loss for Instance Segmentation via k-step Distance Transformation Image	Feb 22, 2021	Instance SegmentationSegmentation	—Unverified
CellTrack R-CNN: A Novel End-To-End Deep Neural Network for Cell Segmentation and Tracking in Microscopy Images	Feb 20, 2021	Cell DetectionCell Segmentation	CodeCode Available
One Shot Model For COVID-19 Classification and Lesions Segmentation In Chest CT Scans Using LSTM With Attention Mechanism	Feb 19, 2021	Instance SegmentationSegmentation	CodeCode Available
One Shot Model For COVID-19 Classification and Lesions Segmentation In Chest CT Scans Using LSTM With Attention Mechanism	Feb 19, 2021	COVID-19 DiagnosisCOVID-19 Image Segmentation	CodeCode Available
EfficientLPS: Efficient LiDAR Panoptic Segmentation	Feb 16, 2021	Autonomous VehiclesInstance Segmentation	—Unverified
Building outline delineation: From aerial images to polygons with an improved end-to-end learning framework	Feb 14, 2021	Instance SegmentationSemantic Segmentation	—Unverified
INSTA-YOLO: Real-Time Instance Segmentation	Feb 12, 2021	GPUInstance Segmentation	—Unverified
Improving Aerial Instance Segmentation in the Dark with Self-Supervised Low Light Enhancement	Feb 10, 2021	Instance SegmentationSemantic Segmentation	—Unverified
Exploiting Depth Information for Wildlife Monitoring	Feb 10, 2021	Depth EstimationInstance Segmentation	CodeCode Available
3D Object Detection and Instance Segmentation from 3D Range and 2D Color Images	Feb 9, 2021	3D Instance Segmentation3D Object Detection	—Unverified
A Histogram Thresholding Improvement to Mask R-CNN for Scalable Segmentation of New and Old Rural Buildings	Feb 8, 2021	Instance SegmentationSegmentation	—Unverified
Instance and Panoptic Segmentation Using Conditional Convolutions	Feb 5, 2021	Instance SegmentationPanoptic Segmentation	—Unverified
Tooth Instance Segmentation from Cone-Beam CT Images through Point-based Detection and Gaussian Disentanglement	Feb 2, 2021	DisentanglementInstance Segmentation	—Unverified
Nondiscriminatory Treatment: a straightforward framework for multi-human parsing	Jan 26, 2021	Human ParsingInstance Segmentation	—Unverified
Self-Supervised Representation Learning from Flow Equivariance	Jan 16, 2021	Instance Segmentationobject-detection	—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