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 1241–1250 of 2262 papers

Title	Date	Tasks	Status	Hype
Instance Segmentation for Autonomous Log Grasping in Forestry Operations	Mar 3, 2022	Inductive BiasInstance Segmentation	CodeCode Available	1
SoftGroup for 3D Instance Segmentation on Point Clouds	Mar 3, 2022	3D Instance Segmentation3D Object Detection	CodeCode Available	2
SEA: Bridging the Gap Between One- and Two-stage Detector Distillation via SEmantic-aware Alignment	Mar 2, 2022	Instance Segmentationobject-detection	—Unverified	0
Colon Nuclei Instance Segmentation using a Probabilistic Two-Stage Detector	Mar 1, 2022	Instance Segmentationobject-detection	—Unverified	0
Simultaneous Semantic and Instance Segmentation for Colon Nuclei Identification and Counting	Mar 1, 2022	Instance SegmentationNuclear Segmentation	CodeCode Available	0
DropIT: Dropping Intermediate Tensors for Memory-Efficient DNN Training	Feb 28, 2022	GPUInstance Segmentation	CodeCode Available	1
ciscNet -- A Single-Branch Cell Instance Segmentation and Classification Network	Feb 25, 2022	ClassificationDecision Making	—Unverified	0
Confidence Calibration for Object Detection and Segmentation	Feb 25, 2022	Autonomous DrivingInstance Segmentation	—Unverified	0
Weakly Supervised Instance Segmentation using Motion Information via Optical Flow	Feb 25, 2022	Instance SegmentationOptical Flow Estimation	—Unverified	0
Efficient Video Segmentation Models with Per-frame Inference	Feb 24, 2022	Image MattingInstance Segmentation	—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