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 2701–2750 of 5035 papers

TitleStatusHype
Training Group Orthogonal Neural Networks with Privileged Information—0
Training Multi-organ Segmentation Networks with Sample Selection by Relaxed Upper Confident Bound—0
Trans2Unet: Neural fusion for Nuclei Semantic Segmentation—0
TransCC: Transformer Network for Coronary Artery CCTA Segmentation—0
TransCut: Transparent Object Segmentation from a Light-Field Image—0
TransDAE: Dual Attention Mechanism in a Hierarchical Transformer for Efficient Medical Image Segmentation—0
Transductive image segmentation: Self-training and effect of uncertainty estimation—0
Brain MRI Tumor Segmentation with Adversarial Networks—0
Transfer Learning for Brain Tumor Segmentation—0
Transfer Learning from Partial Annotations for Whole Brain Segmentation—0
Transferring Knowledge for Food Image Segmentation using Transformers and Convolutions—0
Transferring Ultrahigh-Field Representations for Intensity-Guided Brain Segmentation of Low-Field Magnetic Resonance Imaging—0
Transfer Risk Map: Mitigating Pixel-level Negative Transfer in Medical Segmentation—0
Transformation Consistent Self-ensembling Model for Semi-supervised Medical Image Segmentation—0
Transformer-CNN Fused Architecture for Enhanced Skin Lesion Segmentation—0
Transformers Meet Visual Learning Understanding: A Comprehensive Review—0
Transformer-Unet: Raw Image Processing with Unet—0
Transformer Utilization in Medical Image Segmentation Networks—0
Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectives—0
Transframer: Arbitrary Frame Prediction with Generative Models—0
TransFusion: Multi-view Divergent Fusion for Medical Image Segmentation with Transformers—0
TranSiam: Fusing Multimodal Visual Features Using Transformer for Medical Image Segmentation—0
Transitive Distance Clustering with K-Means Duality—0
TransLandSeg: A Transfer Learning Approach for Landslide Semantic Segmentation Based on Vision Foundation Model—0
TransMedSeg: A Transferable Semantic Framework for Semi-Supervised Medical Image Segmentation—0
Transparency Distortion Robustness for SOTA Image Segmentation Tasks—0
TransUPR: A Transformer-based Uncertain Point Refiner for LiDAR Point Cloud Semantic Segmentation—0
Tree-Cut for Probabilistic Image Segmentation—0
Tree-NET: Enhancing Medical Image Segmentation Through Efficient Low-Level Feature Training—0
TreeSegNet: Adaptive Tree CNNs for Subdecimeter Aerial Image Segmentation—0
TricycleGAN: Unsupervised Image Synthesis and Segmentation Based on Shape Priors—0
Trilateral Attention Network for Real-time Medical Image Segmentation—0
Tri-Plane Mamba: Efficiently Adapting Segment Anything Model for 3D Medical Images—0
Tropical and Extratropical Cyclone Detection Using Deep Learning—0
Trust, but Verify: Robust Image Segmentation using Deep Learning—0
TRUSTED: The Paired 3D Transabdominal Ultrasound and CT Human Data for Kidney Segmentation and Registration Research—0
Trusting Semantic Segmentation Networks—0
Trustworthy Deep Learning for Medical Image Segmentation—0
SUPER-Net: Trustworthy Medical Image Segmentation with Uncertainty Propagation in Encoder-Decoder Networks—0
TSI-Net: A Timing Sequence Image Segmentation Network for Intracranial Artery Segmentation in Digital Subtraction Angiography—0
TSRFormer: Table Structure Recognition with Transformers—0
TSUBF-Net: Trans-Spatial UNet-like Network with Bi-direction Fusion for Segmentation of Adenoid Hypertrophy in CT—0
Tumor-Centered Patching for Enhanced Medical Image Segmentation—0
Tuning a SAM-Based Model with Multi-Cognitive Visual Adapter to Remote Sensing Instance Segmentation—0
TWIG: Two-Step Image Generation using Segmentation Masks in Diffusion Models—0
Two Approaches to Supervised Image Segmentation—0
Two Decades of Colorization and Decolorization for Images and Videos—0
Two layer Ensemble of Deep Learning Models for Medical Image Segmentation—0
Two-stage Joint Transductive and Inductive learning for Nuclei Segmentation—0
Two-stage MR Image Segmentation Method for Brain Tumors based on Attention Mechanism—0
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All datasetsMSD (Mirror Segmentation Dataset)PMDMAS3KPascal Panoptic PartsRMASPASCAL VOCHuTu 80MARIDACOCO val2017ImageNetMSD HeartOxfordPets

Benchmark Results

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