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 1071–1080 of 2262 papers

Title	Date	Tasks	Status	Hype
Single-Stage Open-world Instance Segmentation with Cross-task Consistency Regularization	Aug 18, 2022	Autonomous DrivingInstance Segmentation	CodeCode Available	0
Unifying Visual Perception by Dispersible Points Learning	Aug 18, 2022	Instance SegmentationObject	CodeCode Available	1
Open-Vocabulary Universal Image Segmentation with MaskCLIP	Aug 18, 2022	Image SegmentationInstance Segmentation	CodeCode Available	1
Video-TransUNet: Temporally Blended Vision Transformer for CT VFSS Instance Segmentation	Aug 17, 2022	Instance SegmentationSegmentation	CodeCode Available	1
Look in Different Views: Multi-Scheme Regression Guided Cell Instance Segmentation	Aug 17, 2022	Instance Segmentationregression	—Unverified	0
DeepSportradar-v1: Computer Vision Dataset for Sports Understanding with High Quality Annotations	Aug 17, 2022	Camera CalibrationInstance Segmentation	CodeCode Available	1
FEC: Fast Euclidean Clustering for Point Cloud Segmentation	Aug 16, 2022	ClusteringInstance Segmentation	CodeCode Available	2
Uni6Dv2: Noise Elimination for 6D Pose Estimation	Aug 15, 2022	6D Pose EstimationDenoising	—Unverified	0
Scale-free and Task-agnostic Attack: Generating Photo-realistic Adversarial Patterns with Patch Quilting Generator	Aug 12, 2022	Adversarial AttackImage Classification	—Unverified	0
Collaborative Propagation on Multiple Instance Graphs for 3D Instance Segmentation with Single-point Supervision	Aug 10, 2022	3D Instance SegmentationInstance Segmentation	CodeCode Available	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