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Image segmentation.

Image segmentation is a computer vision technique that divides a digital image into multiple parts or "segments," where each segment contains pixels with similar characteristics, such as color, texture, or brightness. The goal is to simplify an image by changing its representation into something more meaningful and easier to analyze, often by identifying and locating objects, their boundaries, and different regions within the image. This process has wide-ranging applications, from medical image analysis to autonomous vehicles and satellite imagery.

9
Datasets
3
Results
Canonical metric
§ 02 · Canonical benchmark

The reference dataset.

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§ 03 · Top 10

Leading models.

Leading models across all datasets in this task.

#ModelmAPYearSource
Segment Anything Model (SAM)46.5paper ↗
2Segment Anything Model (SAM)44.7paper ↗
3Segment Anything Model (SAM)0.768paper ↗

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§ 04 · All datasets

Tracked datasets.

9 datasets tracked for this task.

BSDS500
1 result
Top: Segment Anything Model (SAM) 0.768
COCO 2017 Instance Segmentation
1 result
Top: Segment Anything Model (SAM) 46.5
LVIS (Instance Segmentation)
1 result
Top: Segment Anything Model (SAM) 44.7
ADE20K
0 results
BRAVO (OOD)
0 results
CityScapes
0 results
LoveDA
0 results
Oxford-IIIT Pets
0 results
PASCAL VOC 2012
0 results
§ 05 · Related tasks

Other tasks in Computer Vision.

3D UnderstandingDepth estimationDocument Image ClassificationDocument Layout AnalysisDocument ParsingDocument UnderstandingGeneral OCR CapabilitiesHandwriting Recognition
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