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 1831–1840 of 2262 papers

Title	Date	Tasks	Status
TreeNet: A lightweight One-Shot Aggregation Convolutional Network	Sep 25, 2021	Instance Segmentationobject-detection	—Unverified
Tuning a SAM-Based Model with Multi-Cognitive Visual Adapter to Remote Sensing Instance Segmentation	Aug 16, 2024	DecoderImage Segmentation	—Unverified
Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations	Jan 30, 2025	Instance SegmentationSemantic Segmentation	—Unverified
Two-Dimensional Quantum Material Identification via Self-Attention and Soft-labeling in Deep Learning	May 31, 2022	2kInstance Segmentation	—Unverified
Two-Step Active Learning for Instance Segmentation with Uncertainty and Diversity Sampling	Sep 28, 2023	Active LearningDiversity	—Unverified
U4D: Unsupervised 4D Dynamic Scene Understanding	Jul 23, 2019	3D Pose EstimationInstance Segmentation	—Unverified
UCP-Net: Unstructured Contour Points for Instance Segmentation	Sep 15, 2021	Instance SegmentationInteractive Segmentation	—Unverified
UDTIRI: An Online Open-Source Intelligent Road Inspection Benchmark Suite	Apr 18, 2023	BenchmarkingInstance Segmentation	—Unverified
UIFormer: A Unified Transformer-based Framework for Incremental Few-Shot Object Detection and Instance Segmentation	Nov 13, 2024	DecoderFew-Shot Object Detection	—Unverified
Uncertainty Aware Active Learning for Reconfiguration of Pre-trained Deep Object-Detection Networks for New Target Domains	Mar 22, 2023	Active LearningInformativeness	—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