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 3901–3950 of 5035 papers

TitleStatusHype
Efficient 3D Instance Mapping and Localization with Neural Fields—0
Efficient and Generic Interactive Segmentation Framework to Correct Mispredictions during Clinical Evaluation of Medical Images—0
Efficient and Invariant Convolutional Neural Networks for Dense Prediction—0
Efficient Bayesian Uncertainty Estimation for nnU-Net—0
Efficient Convolutional Neural Network with Binary Quantization Layer—0
Efficient Energy Minimization for Enforcing Statistics—0
Efficient identification, localization and quantification of grapevine inflorescences in unprepared field images using Fully Convolutional Networks—0
Efficient In-Context Medical Segmentation with Meta-driven Visual Prompt Selection—0
Efficient Information Theoretic Clustering on Discrete Lattices—0
Efficient Knowledge Distillation of SAM for Medical Image Segmentation—0
Efficiently Computing Piecewise Flat Embeddings for Data Clustering and Image Segmentation—0
Efficiently Troubleshooting Image Segmentation Models with Human-In-The-Loop—0
Efficient Medical Image Restoration via Reliability Guided Learning in Frequency Domain—0
Efficient Medical Image Segmentation with Intermediate Supervision Mechanism—0
Efficient Neural Architecture Search on Low-Dimensional Data for OCT Image Segmentation—0
Efficient OCT Image Segmentation Using Neural Architecture Search—0
Efficient Parameter Adaptation for Multi-Modal Medical Image Segmentation and Prognosis—0
Efficient piecewise training of deep structured models for semantic segmentation—0
Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation—0
Efficient Single-Image Depth Estimation on Mobile Devices, Mobile AI & AIM 2022 Challenge: Report—0
Efficient Video Semantic Segmentation with Labels Propagation and Refinement—0
EGMM: an Evidential Version of the Gaussian Mixture Model for Clustering—0
Enhancing CT Image synthesis from multi-modal MRI data based on a multi-task neural network framework—0
EigenRank by Committee: A Data Subset Selection and Failure Prediction paradigm for Robust Deep Learning based Medical Image Segmentation—0
A Region-based Randers Geodesic Approach for Image Segmentation—0
EISeg: An Efficient Interactive Segmentation Tool based on PaddlePaddle—0
Elastic Interaction Energy-Informed Real-Time Traffic Scene Perception—0
ELBO-T2IAlign: A Generic ELBO-Based Method for Calibrating Pixel-level Text-Image Alignment in Diffusion Models—0
ELEV-VISION: Automated Lowest Floor Elevation Estimation from Segmenting Street View Images—0
ELEV-VISION-SAM: Integrated Vision Language and Foundation Model for Automated Estimation of Building Lowest Floor Elevation—0
Embeddings are all you need! Achieving High Performance Medical Image Classification through Training-Free Embedding Analysis—0
Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation—0
EMDS-5: Environmental Microorganism Image Dataset Fifth Version for Multiple Image Analysis Tasks—0
EMDS-6: Environmental Microorganism Image Dataset Sixth Version for Image Denoising, Segmentation, Feature Extraction, Classification and Detection Methods Evaluation—0
EmoCAM: Toward Understanding What Drives CNN-based Emotion Recognition—0
Empirical Analysis of a Segmentation Foundation Model in Prostate Imaging—0
Empirical curvelet based Fully Convolutional Network for supervised texture image segmentation—0
Empirical Evaluation of the Segment Anything Model (SAM) for Brain Tumor Segmentation—0
Enabling Highly Efficient Capsule Networks Processing Through A PIM-Based Architecture Design—0
Encoder-Decoder based CNN and Fully Connected CRFs for Remote Sensed Image Segmentation—0
Encoder-decoder semantic segmentation models for electroluminescence images of thin-film photovoltaic modules—0
Encoder Fusion Network with Co-Attention Embedding for Referring Image Segmentation—0
Endow SAM with Keen Eyes: Temporal-spatial Prompt Learning for Video Camouflaged Object Detection—0
End-to-end autoencoding architecture for the simultaneous generation of medical images and corresponding segmentation masks—0
End-to-End Deep Convolutional Active Contours for Image Segmentation—0
End-to-End Deep Learning of Lane Detection and Path Prediction for Real-Time Autonomous Driving—0
End-to-End Defect Detection in Automated Fiber Placement Based on Artificially Generated Data—0
Brain Segmentation from k-space with End-to-end Recurrent Attention Network—0
End-to-End Trainable Deep Active Contour Models for Automated Image Segmentation: Delineating Buildings in Aerial Imagery—0
Enforcing Perceptual Consistency on Generative Adversarial Networks by Using the Normalised Laplacian Pyramid Distance—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