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Segmentation

Papers

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Showing 451–500 of 13072 papers

TitleStatusHype
Adapter is All You Need for Tuning Visual TasksCode2
Simplifying Object Segmentation with PixelLib LibraryCode2
Deep Hierarchical Semantic SegmentationCode2
SkinMamba: A Precision Skin Lesion Segmentation Architecture with Cross-Scale Global State Modeling and Frequency Boundary GuidanceCode2
Cross-Modal Interactive Perception Network with Mamba for Lung Tumor Segmentation in PET-CT ImagesCode2
SOLOv2: Dynamic and Fast Instance SegmentationCode2
Cross-Image Relational Knowledge Distillation for Semantic SegmentationCode2
SPINEPS -- Automatic Whole Spine Segmentation of T2-weighted MR images using a Two-Phase Approach to Multi-class Semantic and Instance SegmentationCode2
Cell Detection with Star-convex PolygonsCode2
Stable Diffusion Segmentation for Biomedical Images with Single-step Reverse ProcessCode2
Surgical SAM 2: Real-time Segment Anything in Surgical Video by Efficient Frame PruningCode2
Exploiting Scale-Variant Attention for Segmenting Small Medical ObjectsCode2
CellViT: Vision Transformers for Precise Cell Segmentation and ClassificationCode2
Temporal Action Segmentation: An Analysis of Modern TechniquesCode2
CSAD: Unsupervised Component Segmentation for Logical Anomaly DetectionCode2
Text4Seg: Reimagining Image Segmentation as Text GenerationCode2
AgileFormer: Spatially Agile Transformer UNet for Medical Image SegmentationCode2
Centerline Boundary Dice Loss for Vascular SegmentationCode2
The Missing Point in Vision Transformers for Universal Image SegmentationCode2
TokenUnify: Scalable Autoregressive Visual Pre-training with Mixture Token PredictionCode2
MIST: A Simple and Scalable End-To-End 3D Medical Imaging Segmentation FrameworkCode2
CrossEarth: Geospatial Vision Foundation Model for Domain Generalizable Remote Sensing Semantic SegmentationCode2
3D UX-Net: A Large Kernel Volumetric ConvNet Modernizing Hierarchical Transformer for Medical Image SegmentationCode2
Towards Generating Realistic 3D Semantic Training Data for Autonomous DrivingCode2
Customized Segment Anything Model for Medical Image SegmentationCode2
Training-free CryoET Tomogram SegmentationCode2
CGCOD: Class-Guided Camouflaged Object DetectionCode2
Transformer-Based Visual Segmentation: A SurveyCode2
Deep learning-driven pulmonary artery and vein segmentation reveals demography-associated vasculature anatomical differencesCode2
Context-Aware Video Instance SegmentationCode2
A-Eval: A Benchmark for Cross-Dataset Evaluation of Abdominal Multi-Organ SegmentationCode2
Understanding Multi-Granularity for Open-Vocabulary Part SegmentationCode2
Context Encoding for Semantic SegmentationCode2
Aerial Lifting: Neural Urban Semantic and Building Instance Lifting from Aerial ImageryCode2
Constructing and Exploring Intermediate Domains in Mixed Domain Semi-supervised Medical Image SegmentationCode2
UNeXt: MLP-based Rapid Medical Image Segmentation NetworkCode2
UniSeg: A Unified Multi-Modal LiDAR Segmentation Network and the OpenPCSeg CodebaseCode2
Universal Segmentation at Arbitrary Granularity with Language InstructionCode2
Unleashing Text-to-Image Diffusion Models for Visual PerceptionCode2
Co-Occurrent Features in Semantic SegmentationCode2
ClassWise-SAM-Adapter: Parameter Efficient Fine-tuning Adapts Segment Anything to SAR Domain for Semantic SegmentationCode2
Unsupervised Universal Image SegmentationCode2
COB-GS: Clear Object Boundaries in 3DGS Segmentation Based on Boundary-Adaptive Gaussian SplittingCode2
VICRegL: Self-Supervised Learning of Local Visual FeaturesCode2
OBSeg: Accurate and Fast Instance Segmentation Framework Using Segmentation Foundation Models with Oriented Bounding Box PromptsCode2
CMX: Cross-Modal Fusion for RGB-X Semantic Segmentation with TransformersCode2
CoBEVT: Cooperative Bird's Eye View Semantic Segmentation with Sparse TransformersCode2
Computer Vision for Road Imaging and Pothole Detection: A State-of-the-Art Review of Systems and AlgorithmsCode2
CorrCLIP: Reconstructing Correlations in CLIP with Off-the-Shelf Foundation Models for Open-Vocabulary Semantic SegmentationCode2
Deep Spectral Methods: A Surprisingly Strong Baseline for Unsupervised Semantic Segmentation and LocalizationCode2
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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