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

Showing 151200 of 5035 papers

TitleStatusHype
Tyche: Stochastic In-Context Learning for Medical Image SegmentationCode2
PA-SAM: Prompt Adapter SAM for High-Quality Image SegmentationCode2
PMFSNet: Polarized Multi-scale Feature Self-attention Network For Lightweight Medical Image SegmentationCode2
Seg-metrics: a Python package to compute segmentation metricsCode2
U-Mamba: Enhancing Long-range Dependency for Biomedical Image SegmentationCode2
Deep Covariance Alignment for Domain Adaptive Remote Sensing Image SegmentationCode2
BRAU-Net++: U-Shaped Hybrid CNN-Transformer Network for Medical Image SegmentationCode2
Rethinking Interactive Image Segmentation with Low Latency High Quality and Diverse PromptsCode2
Unsupervised Universal Image SegmentationCode2
UniRef++: Segment Every Reference Object in Spatial and Temporal SpacesCode2
Narrowing the semantic gaps in U-Net with learnable skip connections: The case of medical image segmentationCode2
SegRefiner: Towards Model-Agnostic Segmentation Refinement with Discrete Diffusion ProcessCode2
MCANet: Medical Image Segmentation with Multi-Scale Cross-Axis AttentionCode2
ScribblePrompt: Fast and Flexible Interactive Segmentation for Any Biomedical ImageCode2
SegVol: Universal and Interactive Volumetric Medical Image SegmentationCode2
Open-Vocabulary Camouflaged Object SegmentationCode2
Medical Image Segmentation with Domain Adaptation: A SurveyCode2
SAM-Med3D: Towards General-purpose Segmentation Models for Volumetric Medical ImagesCode2
CLIPSelf: Vision Transformer Distills Itself for Open-Vocabulary Dense PredictionCode2
nnSAM: Plug-and-play Segment Anything Model Improves nnUNet PerformanceCode2
Beyond Adapting SAM: Towards End-to-End Ultrasound Image Segmentation via Auto PromptingCode2
Beyond Self-Attention: Deformable Large Kernel Attention for Medical Image SegmentationCode2
Tiny and Efficient Model for the Edge Detection GeneralizationCode2
EGE-UNet: an Efficient Group Enhanced UNet for skin lesion segmentationCode2
Hierarchical Open-vocabulary Universal Image SegmentationCode2
MIS-FM: 3D Medical Image Segmentation using Foundation Models Pretrained on a Large-Scale Unannotated DatasetCode2
RSPrompter: Learning to Prompt for Remote Sensing Instance Segmentation based on Visual Foundation ModelCode2
MedLSAM: Localize and Segment Anything Model for 3D CT ImagesCode2
3DSAM-adapter: Holistic adaptation of SAM from 2D to 3D for promptable tumor segmentationCode2
SAM3D: Zero-Shot 3D Object Detection via Segment Anything ModelCode2
Contextual Object Detection with Multimodal Large Language ModelsCode2
SSSegmenation: An Open Source Supervised Semantic Segmentation Toolbox Based on PyTorchCode2
Bidirectional Copy-Paste for Semi-Supervised Medical Image SegmentationCode2
EasyPortrait -- Face Parsing and Portrait Segmentation DatasetCode2
Customized Segment Anything Model for Medical Image SegmentationCode2
Domain Adaptive and Generalizable Network Architectures and Training Strategies for Semantic Image SegmentationCode2
UniverSeg: Universal Medical Image SegmentationCode2
SAMM (Segment Any Medical Model): A 3D Slicer Integration to SAMCode2
Unifying and Personalizing Weakly-supervised Federated Medical Image Segmentation via Adaptive Representation and AggregationCode2
Ambiguous Medical Image Segmentation using Diffusion ModelsCode2
CAT-Seg: Cost Aggregation for Open-Vocabulary Semantic SegmentationCode2
M^2SNet: Multi-scale in Multi-scale Subtraction Network for Medical Image SegmentationCode2
MedNeXt: Transformer-driven Scaling of ConvNets for Medical Image SegmentationCode2
Unleashing Text-to-Image Diffusion Models for Visual PerceptionCode2
Deep Incubation: Training Large Models by Divide-and-ConqueringCode2
UNETR++: Delving into Efficient and Accurate 3D Medical Image SegmentationCode2
Medical Image Segmentation Review: The success of U-NetCode2
SimpleClick: Interactive Image Segmentation with Simple Vision TransformersCode2
3D UX-Net: A Large Kernel Volumetric ConvNet Modernizing Hierarchical Transformer for Medical Image SegmentationCode2
Understanding the Tricks of Deep Learning in Medical Image Segmentation: Challenges and Future DirectionsCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SAM2-UNetIoU0.92Unverified
2HetNetIoU0.83Unverified
3PMDIoU0.82Unverified
4SANetIoU0.8Unverified
5MirrorNetIoU0.79Unverified
#ModelMetricClaimedVerifiedStatus
1SAM2-UNetIoU0.73Unverified
2HetNetIoU0.69Unverified
3SANetIoU0.67Unverified
4PMDIoU0.66Unverified
5MirrorNetIoU0.59Unverified
#ModelMetricClaimedVerifiedStatus
1SAM2-UNetmIoU0.8Unverified
2MAS-SAMmIoU0.79Unverified
3MASNetmIoU0.74Unverified
4ZoomNetmIoU0.74Unverified
#ModelMetricClaimedVerifiedStatus
1HIPIE (ViT-H)mIoUPartS63.8Unverified
2PPSmIoUPartS58.6Unverified
3HIPIE (ResNet-50)mIoUPartS57.2Unverified
4JPPFmIoUPartS54.4Unverified
#ModelMetricClaimedVerifiedStatus
1MAS-SAMmIoU0.74Unverified
2SAM2-UNetmIoU0.74Unverified
3MASNetmIoU0.73Unverified
4ZoomNetmIoU0.73Unverified
#ModelMetricClaimedVerifiedStatus
1OneNete,4-CmIoU63.6Unverified
2OneNete,4-SmAP0.552.75Unverified
3OneNeted,4mIoU14.9Unverified
#ModelMetricClaimedVerifiedStatus
1UNetRDice0.98Unverified
2PALEDDice0.98Unverified
#ModelMetricClaimedVerifiedStatus
1ResAttUNetIoU0.67Unverified
2UNetIoU0.57Unverified
#ModelMetricClaimedVerifiedStatus
1SynCo (ResNet-50) 200epmask AP35.4Unverified
#ModelMetricClaimedVerifiedStatus
1MobileOne-S0GFLOPs0.28Unverified
#ModelMetricClaimedVerifiedStatus
1OneNete,4mIoU6.6Unverified
#ModelMetricClaimedVerifiedStatus
1OneNete,4-CDice Score0.97Unverified