SOTAVerified

Image Segmentation

Image Segmentation is a computer vision task that involves dividing an image into multiple segments or regions, each of which corresponds to a different object or part of an object. The goal of image segmentation is to assign a unique label or category to each pixel in the image, so that pixels with similar attributes are grouped together.

Papers

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Showing 1–10 of 5035 papers

TitleStatusHype
DiffOSeg: Omni Medical Image Segmentation via Multi-Expert Collaboration Diffusion ModelCode0
Unified Medical Image Segmentation with State Space Modeling Snake—0
Alleviating Textual Reliance in Medical Language-guided Segmentation via Prototype-driven Semantic ApproximationCode2
U-RWKV: Lightweight medical image segmentation with direction-adaptive RWKVCode1
A New Dataset and Performance Benchmark for Real-time Spacecraft Segmentation in Onboard Flight ComputersCode0
Prompt Engineering in Segment Anything Model: Methodologies, Applications, and Emerging Challenges—0
Admissibility of Stein Shrinkage for Batch Normalization in the Presence of Adversarial Attacks—0
HNOSeg-XS: Extremely Small Hartley Neural Operator for Efficient and Resolution-Robust 3D Image SegmentationCode0
Rethinking Query-based Transformer for Continual Image SegmentationCode1
Just Say Better or Worse: A Human-AI Collaborative Framework for Medical Image Segmentation Without Manual Annotations—0
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All datasetsMSD (Mirror Segmentation Dataset)PMDMAS3KPascal Panoptic PartsRMASPASCAL VOCHuTu 80MARIDACOCO val2017ImageNetMSD HeartOxfordPets

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SAM2-UNetIoU0.73—Unverified
2HetNetIoU0.69—Unverified
3SANetIoU0.67—Unverified
4PMDIoU0.66—Unverified
5MirrorNetIoU0.59—Unverified