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 14011425 of 5035 papers

TitleStatusHype
Multimodal-Aware Fusion Network for Referring Remote Sensing Image SegmentationCode0
Diff-CL: A Novel Cross Pseudo-Supervision Method for Semi-supervised Medical Image Segmentation0
SeqSAM: Autoregressive Multiple Hypothesis Prediction for Medical Image Segmentation using SAMCode0
GIGP: A Global Information Interacting and Geometric Priors Focusing Framework for Semi-supervised Medical Image Segmentation0
QuickDraw: Fast Visualization, Analysis and Active Learning for Medical Image SegmentationCode0
3D Medical Imaging Segmentation on Non-Contrast CT0
On the status of current quantum machine learning software0
MaskAttn-UNet: A Mask Attention-Driven Framework for Universal Low-Resolution Image Segmentation0
Task-Specific Knowledge Distillation from the Vision Foundation Model for Enhanced Medical Image Segmentation0
MIRAM: Masked Image Reconstruction Across Multiple Scales for Breast Lesion Risk Prediction0
QuantU-Net: Efficient Wearable Medical Imaging Using Bitwidth as a Trainable Parameter0
Visual and Text Prompt Segmentation: A Novel Multi-Model Framework for Remote Sensing0
Customized SAM 2 for Referring Remote Sensing Image Segmentation0
Semi-Supervised Medical Image Segmentation via Knowledge Mining from Large Models0
Continuous Online Adaptation Driven by User Interaction for Medical Image Segmentation0
Dynamically evolving segment anything model with continuous learning for medical image segmentation0
Towards Universal Text-driven CT Image SegmentationCode0
A Label-Free High-Precision Residual Moveout Picking Method for Travel Time Tomography based on Deep Learning0
Conformal Prediction for Image Segmentation Using Morphological Prediction SetsCode0
Disconnect to Connect: A Data Augmentation Method for Improving Topology Accuracy in Image SegmentationCode0
Partially Supervised Unpaired Multi-Modal Learning for Label-Efficient Medical Image Segmentation0
Gaussian Random Fields as an Abstract Representation of Patient Metadata for Multimodal Medical Image SegmentationCode0
We Care Each Pixel: Calibrating on Medical Segmentation ModelCode0
S4M: Segment Anything with 4 Extreme Points0
Enhancing SAM with Efficient Prompting and Preference Optimization for Semi-supervised Medical Image Segmentation0
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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