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 921–930 of 2262 papers

Title	Date	Tasks	Status	Score
Gated Channel Transformation for Visual Recognition	Sep 25, 2019	General Classificationimage-classification	CodeCode Available	5
Assessment of Cell Nuclei AI Foundation Models in Kidney Pathology	Aug 9, 2024	Instance SegmentationSegmentation	CodeCode Available	5
Pixelwise Instance Segmentation with a Dynamically Instantiated Network	Apr 7, 2017	Instance SegmentationObject	CodeCode Available	5
PM-VIS+: High-Performance Video Instance Segmentation without Video Annotation	Jun 28, 2024	Instance SegmentationSegmentation	CodeCode Available	5
Pixel-Level Analysis for Enhancing Threat Detection in Large-Scale X-ray Security Images	Nov 1, 2021	Instance SegmentationSemantic Segmentation	CodeCode Available	5
SAM-PD: How Far Can SAM Take Us in Tracking and Segmenting Anything in Videos by Prompt Denoising	Mar 7, 2024	DenoisingInstance Segmentation	CodeCode Available	5
PersonLab: Person Pose Estimation and Instance Segmentation with a Bottom-Up, Part-Based, Geometric Embedding Model	Mar 22, 2018	Instance SegmentationKeypoint Detection	CodeCode Available	5
From Seedling to Harvest: The GrowingSoy Dataset for Weed Detection in Soy Crops via Instance Segmentation	Jun 1, 2024	image-classificationImage Classification	CodeCode Available	5
ClusterFuG: Clustering Fully connected Graphs by Multicut	Jan 28, 2023	ClusteringGraph Clustering	CodeCode Available	5
3D-SIS: 3D Semantic Instance Segmentation of RGB-D Scans	Dec 17, 2018	3D Instance Segmentation3D Object Detection	CodeCode Available	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