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 1181–1190 of 2262 papers

Title	Date	Tasks	Status	Hype
Monocular Depth Estimation Using Cues Inspired by Biological Vision Systems	Apr 21, 2022	Depth EstimationDepth Prediction	CodeCode Available	0
Unseen Object Instance Segmentation with Fully Test-time RGB-D Embeddings Adaptation	Apr 21, 2022	Instance SegmentationKnowledge Distillation	—Unverified	0
Shape-Aware Monocular 3D Object Detection	Apr 19, 2022	3D Object DetectionInstance Segmentation	—Unverified	0
Modeling Missing Annotations for Incremental Learning in Object Detection	Apr 19, 2022	Incremental LearningInstance Segmentation	CodeCode Available	1
Less than Few: Self-Shot Video Instance Segmentation	Apr 19, 2022	Few-Shot LearningInstance Segmentation	—Unverified	0
Temporally Efficient Vision Transformer for Video Instance Segmentation	Apr 18, 2022	Instance SegmentationSemantic Segmentation	CodeCode Available	2
VSA: Learning Varied-Size Window Attention in Vision Transformers	Apr 18, 2022	Instance SegmentationObject Detection	CodeCode Available	2
An Extendable, Efficient and Effective Transformer-based Object Detector	Apr 17, 2022	Decoderimage-classification	—Unverified	0
Transfer Learning for Instance Segmentation of Waste Bottles using Mask R-CNN Algorithm	Apr 15, 2022	Instance SegmentationRegion Proposal	—Unverified	0
Invisible-to-Visible: Privacy-Aware Human Instance Segmentation using Airborne Ultrasound via Collaborative Learning Variational Autoencoder	Apr 15, 2022	Action RecognitionAction Understanding	—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