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 301–310 of 2262 papers

Title	Date	Tasks	Status	Hype	Score
Exploring Data-Efficient 3D Scene Understanding with Contrastive Scene Contexts	Dec 16, 2020	3D Semantic SegmentationInstance Segmentation	CodeCode Available	1	5
Detection and Segmentation of Custom Objects using High Distraction Photorealistic Synthetic Data	Jul 28, 2020	Instance SegmentationObject Detection	CodeCode Available	1	5
HCFormer: Unified Image Segmentation with Hierarchical Clustering	May 20, 2022	ClusteringImage Segmentation	CodeCode Available	1	5
Clustering Plotted Data by Image Segmentation	Oct 6, 2021	ClusteringImage Segmentation	CodeCode Available	1	5
Combinatorial Optimization for Panoptic Segmentation: A Fully Differentiable Approach	Jun 6, 2021	Combinatorial OptimizationInstance Segmentation	CodeCode Available	1	5
Expediting Large-Scale Vision Transformer for Dense Prediction without Fine-tuning	Oct 3, 2022	ClusteringDepth Estimation	CodeCode Available	1	5
Equalization Loss v2: A New Gradient Balance Approach for Long-tailed Object Detection	Dec 15, 2020	Instance SegmentationLong-tailed Object Detection	CodeCode Available	1	5
Boundary-assisted Region Proposal Networks for Nucleus Segmentation	Jun 4, 2020	Boundary DetectionInstance Segmentation	CodeCode Available	1	5
Boundary-aware Contrastive Learning for Semi-supervised Nuclei Instance Segmentation	Feb 7, 2024	Contrastive LearningDenoising	CodeCode Available	1	5
CLIP-VIS: Adapting CLIP for Open-Vocabulary Video Instance Segmentation	Mar 19, 2024	DecoderInstance Segmentation	CodeCode Available	1	5

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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