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 601–610 of 2262 papers

Title	Date	Tasks	Status	Hype	Score
Deep learning approaches to building rooftop thermal bridge detection from aerial images	Dec 12, 2022	Instance SegmentationObject Detection	CodeCode Available	1	5
Dynamic Convolution for 3D Point Cloud Instance Segmentation	Jul 18, 2021	Instance SegmentationSemantic Segmentation	CodeCode Available	1	5
DIOD: Self-Distillation Meets Object Discovery	Jan 1, 2024	Instance SegmentationKnowledge Distillation	CodeCode Available	1	5
DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision	May 13, 2021	Box-supervised Instance SegmentationInstance Segmentation	CodeCode Available	1	5
FinnWoodlands Dataset	Apr 3, 2023	Autonomous DrivingDepth Completion	CodeCode Available	1	5
Fine-Grained Vehicle Perception via 3D Part-Guided Visual Data Augmentation	Dec 15, 2020	Autonomous DrivingData Augmentation	CodeCode Available	1	5
mc-BEiT: Multi-choice Discretization for Image BERT Pre-training	Mar 29, 2022	Instance Segmentationobject-detection	CodeCode Available	1	5
DyCo3D: Robust Instance Segmentation of 3D Point Clouds through Dynamic Convolution	Nov 26, 2020	3D Instance SegmentationInstance Segmentation	CodeCode Available	1	5
DVIS++: Improved Decoupled Framework for Universal Video Segmentation	Dec 20, 2023	Contrastive LearningDenoising	CodeCode Available	1	5
DynaMask: Dynamic Mask Selection for Instance Segmentation	Mar 14, 2023	Instance SegmentationSegmentation	CodeCode Available	1	5

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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