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 701725 of 5035 papers

TitleStatusHype
Leveraging SAM for Single-Source Domain Generalization in Medical Image SegmentationCode1
CheXseg: Combining Expert Annotations with DNN-generated Saliency Maps for X-ray SegmentationCode1
Alternate Diverse Teaching for Semi-supervised Medical Image SegmentationCode1
DeformUX-Net: Exploring a 3D Foundation Backbone for Medical Image Segmentation with Depthwise Deformable ConvolutionCode1
Beyond One-to-One: Rethinking the Referring Image SegmentationCode1
Deformation-Recovery Diffusion Model (DRDM): Instance Deformation for Image Manipulation and SynthesisCode1
DeiSAM: Segment Anything with Deictic PromptingCode1
Beyond pixel-wise supervision for segmentation: A few global shape descriptors might be surprisingly good!Code1
Delving into Shape-aware Zero-shot Semantic SegmentationCode1
GPU-Net: Lightweight U-Net with more diverse featuresCode1
Gradient Alignment Improves Test-Time Adaptation for Medical Image SegmentationCode1
Latent Diffusion for Medical Image Segmentation: End to end learning for fast sampling and accuracyCode1
Attentive Symmetric Autoencoder for Brain MRI SegmentationCode1
Bi-Directional ConvLSTM U-Net with Densley Connected ConvolutionsCode1
Attention U-Net: Learning Where to Look for the PancreasCode1
Bidirectional Learning for Domain Adaptation of Semantic SegmentationCode1
DeSAM: Decoupled Segment Anything Model for Generalizable Medical Image SegmentationCode1
DeRIS: Decoupling Perception and Cognition for Enhanced Referring Image Segmentation through Loopback SynergyCode1
ALPS: An Auto-Labeling and Pre-training Scheme for Remote Sensing Segmentation With Segment Anything ModelCode1
Adapt Everywhere: Unsupervised Adaptation of Point-Clouds and Entropy Minimisation for Multi-modal Cardiac Image SegmentationCode1
A Location-Sensitive Local Prototype Network for Few-Shot Medical Image SegmentationCode1
Bi-level Learning of Task-Specific Decoders for Joint Registration and One-Shot Medical Image SegmentationCode1
Channel prior convolutional attention for medical image segmentationCode1
Lung Segmentation from Chest X-rays using Variational Data ImputationCode1
CHeart: A Conditional Spatio-Temporal Generative Model for Cardiac AnatomyCode1
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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