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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 191–200 of 2262 papers

Title	Date	Tasks	Status	Hype
Heuristical Comparison of Vision Transformers Against Convolutional Neural Networks for Semantic Segmentation on Remote Sensing Imagery	Nov 14, 2024	image-classificationImage Classification	CodeCode Available	0
UIFormer: A Unified Transformer-based Framework for Incremental Few-Shot Object Detection and Instance Segmentation	Nov 13, 2024	DecoderFew-Shot Object Detection	—Unverified	0
Horticultural Temporal Fruit Monitoring via 3D Instance Segmentation and Re-Identification using Point Clouds	Nov 12, 2024	3D Instance SegmentationInstance Segmentation	CodeCode Available	0
Data-Centric Learning Framework for Real-Time Detection of Aiming Beam in Fluorescence Lifetime Imaging Guided Surgery	Nov 11, 2024	Computational EfficiencyInstance Segmentation	—Unverified	0
Fast and Efficient Transformer-based Method for Bird's Eye View Instance Prediction	Nov 11, 2024	Autonomous VehiclesInstance Segmentation	CodeCode Available	1
SA3DIP: Segment Any 3D Instance with Potential 3D Priors	Nov 6, 2024	3D Instance SegmentationInstance Segmentation	CodeCode Available	0
Tree level change detection over Ahmedabad city using very high resolution satellite images and Deep Learning	Nov 4, 2024	Change DetectionInstance Segmentation	—Unverified	0
MSTA3D: Multi-scale Twin-attention for 3D Instance Segmentation	Nov 4, 2024	3D Instance SegmentationInstance Segmentation	—Unverified	0
Automated Classification of Cell Shapes: A Comparative Evaluation of Shape Descriptors	Nov 1, 2024	Instance SegmentationSemantic Segmentation	CodeCode Available	1
MV-Adapter: Enhancing Underwater Instance Segmentation via Adaptive Channel Attention	Nov 1, 2024	Instance SegmentationSegmentation	—Unverified	0

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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