SOTAVerified

Segmentation

Papers

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Showing 9451–9500 of 13072 papers

TitleStatusHype
SegGen: Supercharging Segmentation Models with Text2Mask and Mask2Img Synthesis—0
SegGPT: Towards Segmenting Everything in Context—0
SegHeD: Segmentation of Heterogeneous Data for Multiple Sclerosis Lesions with Anatomical Constraints—0
SegHeD+: Segmentation of Heterogeneous Data for Multiple Sclerosis Lesions with Anatomical Constraints and Lesion-aware Augmentation—0
SegICL: A Multimodal In-context Learning Framework for Enhanced Segmentation in Medical Imaging—0
SegLLM: Multi-round Reasoning Segmentation—0
SegLoc: Learning Segmentation-Based Representations for Privacy-Preserving Visual Localization—0
SegMatch: A semi-supervised learning method for surgical instrument segmentation—0
SEGMENT3D: A Web-based Application for Collaborative Segmentation of 3D images used in the Shoot Apical Meristem—0
Segment3D: Learning Fine-Grained Class-Agnostic 3D Segmentation without Manual Labels—0
Segmentação e contagem de troncos de madeira utilizando deep learning e processamento de imagens—0
Segmental Audio Word2Vec: Representing Utterances as Sequences of Vectors with Applications in Spoken Term Detection—0
Segment (Almost) Nothing: Prompt-Agnostic Adversarial Attacks on Segmentation Models—0
Segmental Spatiotemporal CNNs for Fine-grained Action Segmentation—0
Segment Any 3D Gaussians—0
Segment Any 4D Gaussians—0
Segment Any Architectural Facades (SAAF):An automatic segmentation model for building facades, walls and windows based on multimodal semantics guidance—0
Segment Any Building—0
Segment Any Cell: A SAM-based Auto-prompting Fine-tuning Framework for Nuclei Segmentation—0
Segment Any Class (SAC): Multi-Class Few-Shot Semantic Segmentation via Class Region Proposals—0
Segment Any Crack: Deep Semantic Segmentation Adaptation for Crack Detection—0
Segment Any Motion in Videos—0
Segment Any Object Model (SAOM): Real-to-Simulation Fine-Tuning Strategy for Multi-Class Multi-Instance Segmentation—0
Segment Any-Quality Images with Generative Latent Space Enhancement—0
Segment Any RGB-Thermal Model with Language-aided Distillation—0
Segment Anything, Even Occluded—0
Segment Anything for Microscopy—0
Segment anything, from space?—0
Segment Anything in Pathology Images with Natural Language—0
Segment Anything is A Good Pseudo-label Generator for Weakly Supervised Semantic Segmentation—0
Segment Anything Meets Semantic Communication—0
Segment Anything Model for automated image data annotation: empirical studies using text prompts from Grounding DINO—0
Segment Anything Model for Brain Tumor Segmentation—0
Pedestrian Accessible Infrastructure Inventory: Assessing Zero-Shot Segmentation on Multi-Mode Geospatial Data for All Pedestrian Types—0
Segment Anything Model-guided Collaborative Learning Network for Scribble-supervised Polyp Segmentation—0
Segment Anything Model (SAM) for Digital Pathology: Assess Zero-shot Segmentation on Whole Slide Imaging—0
Segment Anything Model (SAM) for Radiation Oncology—0
Segment Anything Model (SAM) Meets Glass: Mirror and Transparent Objects Cannot Be Easily Detected—0
Enhancing the Reliability of Segment Anything Model for Auto-Prompting Medical Image Segmentation with Uncertainty Rectification—0
SegmentAnyTree: A sensor and platform agnostic deep learning model for tree segmentation using laser scanning data—0
Segmentasi Citra Menggunakan Metode Watershed Transform Berdasarkan Image Enhancement Dalam Mendeteksi Embrio Telur—0
Segmentation Analysis in Human Centric Cyber-Physical Systems using Graphical Lasso—0
Segmentation and Characterization of Macerated Fibers and Vessels Using Deep Learning—0
Segmentation and Classification of Cine-MR Images Using Fully Convolutional Networks and Handcrafted Features—0
Segmentation and Classification of Skin Lesions for Disease Diagnosis—0
Segmentation and genome annotation algorithms—0
Segmentation and Restoration of Images on Surfaces by Parametric Active Contours with Topology Changes—0
Segmentation and Risk Score Prediction of Head and Neck Cancers in PET/CT Volumes with 3D U-Net and Cox Proportional Hazard Neural Networks—0
Segmentation and Vascular Vectorization for Coronary Artery by Geometry-based Cascaded Neural Network—0
Segmentation Approach for Coreference Resolution Task—0
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All datasetsSA-1B.MFSDMMFloodSimGas

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1unSAM+ (Semi-supervised)Average Precision42.8—Unverified
2SAMAverage Precision38.9—Unverified
#ModelMetricClaimedVerifiedStatus
1HNN10%20—Unverified
#ModelMetricClaimedVerifiedStatus
1ABANetF1 Score96.82—Unverified
#ModelMetricClaimedVerifiedStatus
1ResNet50 + DeepLabV3+F1 score0.77—Unverified
#ModelMetricClaimedVerifiedStatus
1LangGasIoU0.69—Unverified