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 476500 of 5035 papers

TitleStatusHype
Enhancing Organ at Risk Segmentation with Improved Deep Neural NetworksCode1
DA-TransUNet: Integrating Spatial and Channel Dual Attention with Transformer U-Net for Medical Image SegmentationCode1
Argmax Flows and Multinomial Diffusion: Learning Categorical DistributionsCode1
Mutual Consistency Learning for Semi-supervised Medical Image SegmentationCode1
Encoder-Decoder with Atrous Separable Convolution for Semantic Image SegmentationCode1
IFSeg: Image-free Semantic Segmentation via Vision-Language ModelCode1
Decomposing 3D Scenes into Objects via Unsupervised Volume SegmentationCode1
Enhancing Medical Image Segmentation with TransCeption: A Multi-Scale Feature Fusion ApproachCode1
Decoupled Seg Tokens Make Stronger Reasoning Video Segmenter and GrounderCode1
Enhancing Pseudo Label Quality for Semi-Supervised Domain-Generalized Medical Image SegmentationCode1
Deep clustering: Discriminative embeddings for segmentation and separationCode1
A context based deep learning approach for unbalanced medical image segmentationCode1
An Auto-Encoder Strategy for Adaptive Image SegmentationCode1
Bridging the Domain Gap: Self-Supervised 3D Scene Understanding with Foundation ModelsCode1
3DConvCaps: 3DUnet with Convolutional Capsule Encoder for Medical Image SegmentationCode1
From Claims to Evidence: A Unified Framework and Critical Analysis of CNN vs. Transformer vs. Mamba in Medical Image SegmentationCode1
DeepCut: Unsupervised Segmentation using Graph Neural Networks ClusteringCode1
A self-supervised learning strategy for postoperative brain cavity segmentation simulating resectionsCode1
Deep Domain Adaptation: A Sim2Real Neural Approach for Improving Eye-Tracking SystemsCode1
A hierarchical semantic segmentation framework for computer vision-based bridge damage detectionCode1
ACTION++: Improving Semi-supervised Medical Image Segmentation with Adaptive Anatomical ContrastCode1
A high-order focus interaction model and oral ulcer dataset for oral ulcer segmentationCode1
Anatomy of Domain Shift Impact on U-Net Layers in MRI SegmentationCode1
A Simple and Robust Framework for Cross-Modality Medical Image Segmentation applied to Vision TransformersCode1
BT-Unet: A self-supervised learning framework for biomedical image segmentation using Barlow Twins with U-Net modelsCode1
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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