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 2181–2190 of 2262 papers

Title	Date	Tasks	Status
Tree level change detection over Ahmedabad city using very high resolution satellite images and Deep Learning	Nov 4, 2024	Change DetectionInstance Segmentation	—Unverified
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

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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