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 81–90 of 2262 papers

Title	Date	Tasks	Status	Hype
SHViT: Single-Head Vision Transformer with Memory Efficient Macro Design	Jan 29, 2024	CPUGPU	CodeCode Available	2
Rethinking Patch Dependence for Masked Autoencoders	Jan 25, 2024	DecoderInstance Segmentation	CodeCode Available	2
A Simple Latent Diffusion Approach for Panoptic Segmentation and Mask Inpainting	Jan 18, 2024	Instance SegmentationInteractive Segmentation	CodeCode Available	2
OBSeg: Accurate and Fast Instance Segmentation Framework Using Segmentation Foundation Models with Oriented Bounding Box Prompts	Jan 16, 2024	Amodal Instance SegmentationInstance Segmentation	CodeCode Available	2
PartSTAD: 2D-to-3D Part Segmentation Task Adaptation	Jan 11, 2024	3D Part SegmentationForeground Segmentation	CodeCode Available	2
ODIN: A Single Model for 2D and 3D Segmentation	Jan 4, 2024	3D Instance Segmentation3D Semantic Segmentation	CodeCode Available	2
Unsupervised Universal Image Segmentation	Dec 28, 2023	Image SegmentationInstance Segmentation	CodeCode Available	2
SegRefiner: Towards Model-Agnostic Segmentation Refinement with Discrete Diffusion Process	Dec 19, 2023	DenoisingDichotomous Image Segmentation	CodeCode Available	2
SAM-6D: Segment Anything Model Meets Zero-Shot 6D Object Pose Estimation	Nov 27, 2023	6D Pose Estimation using RGBInstance Segmentation	CodeCode Available	2
Adapter is All You Need for Tuning Visual Tasks	Nov 25, 2023	Allimage-classification	CodeCode Available	2

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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	GLEE-Pro	mask AP	54.2	—	Unverified
9	ViT-Adapter-L (HTC++, BEiTv2, O365, multi-scale)	mask AP	54.2	—	Unverified
10	SwinV2-G (HTC++)	mask AP	53.7	—	Unverified