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Semantic Segmentation

Papers

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Showing 3951–4000 of 14763 papers

TitleStatusHype
GeoSAM: Fine-tuning SAM with Multi-Modal Prompts for Mobility Infrastructure SegmentationCode1
Low-Precision Floating-Point for Efficient On-Board Deep Neural Network Processing—0
Synthetic Data Generation for Bridging Sim2Real Gap in a Production Environment—0
On the Out of Distribution Robustness of Foundation Models in Medical Image Segmentation—0
Automatic measurement of coverage area of water-based pesticides-surfactant formulation on plant leaves using deep learning tools—0
Labeling Indoor Scenes with Fusion of Out-of-the-Box Perception Models—0
Zero-Shot Digital Rock Image Segmentation with a Fine-Tuned Segment Anything Model—0
WATUNet: A Deep Neural Network for Segmentation of Volumetric Sweep Imaging Ultrasound—0
ToSkA: Topological Skeleton Analysis for Network-Based Shape Representation and Evaluation of Objects from Cells to Death Stars—0
Shifting to Machine Supervision: Annotation-Efficient Semi and Self-Supervised Learning for Automatic Medical Image Segmentation and ClassificationCode0
Self-trained Panoptic Segmentation—0
Pseudo Label-Guided Data Fusion and Output Consistency for Semi-Supervised Medical Image SegmentationCode0
Versatile Medical Image Segmentation Learned from Multi-Source Datasets via Model Self-DisambiguationCode1
A Framework of Landsat-8 Band Selection based on UMDA for Deforestation Detection—0
Enhancing the Reliability of Segment Anything Model for Auto-Prompting Medical Image Segmentation with Uncertainty Rectification—0
UniMOS: A Universal Framework For Multi-Organ Segmentation Over Label-Constrained DatasetsCode0
MSE-Nets: Multi-annotated Semi-supervised Ensemble Networks for Improving Segmentation of Medical Image with Ambiguous Boundaries—0
End-to-end autoencoding architecture for the simultaneous generation of medical images and corresponding segmentation masks—0
On the Overconfidence Problem in Semantic 3D MappingCode1
PWISeg: Point-based Weakly-supervised Instance Segmentation for Surgical InstrumentsCode0
Slide-SAM: Medical SAM Meets Sliding WindowCode1
VertDetect: Fully End-to-End 3D Vertebral Instance Segmentation Model—0
NormNet: Scale Normalization for 6D Pose Estimation in Stacked Scenarios—0
Nondestructive, quantitative viability analysis of 3D tissue cultures using machine learning image segmentation—0
Correlation-aware active learning for surgery video segmentation—0
Two-stage Joint Transductive and Inductive learning for Nuclei Segmentation—0
Efficient Rotation Invariance in Deep Neural Networks through Artificial Mental Rotation—0
LocaliseBot: Multi-view 3D object localisation with differentiable rendering for robot grasping—0
Test-Time Training for Semantic Segmentation with Output Contrastive LossCode0
SAMIHS: Adaptation of Segment Anything Model for Intracranial Hemorrhage SegmentationCode1
Zero-Shot Segmentation of Eye Features Using the Segment Anything Model (SAM)Code0
Level Set KSVD—0
USLR: an open-source tool for unbiased and smooth longitudinal registration of brain MRCode0
Assessing Test-time Variability for Interactive 3D Medical Image Segmentation with Diverse Point PromptsCode0
Temporal Performance Prediction for Deep Convolutional Long Short-Term Memory Networks—0
Simultaneous Clutter Detection and Semantic Segmentation of Moving Objects for Automotive Radar Data—0
PICS in Pics: Physics Informed Contour Selection for Rapid Image Segmentation—0
Robust semi-supervised segmentation with timestep ensembling diffusion models—0
SpectralGPT: Spectral Remote Sensing Foundation ModelCode2
Sketch-based Video Object Segmentation: Benchmark and Analysis—0
Pruning random resistive memory for optimizing analogue AI—0
Osteoporosis Prediction from Hand and Wrist X-rays using Image Segmentation and Self-Supervised Learning—0
FDNet: Feature Decoupled Segmentation Network for Tooth CBCT Image—0
3DFusion, A real-time 3D object reconstruction pipeline based on streamed instance segmented data—0
IODeep: an IOD for the introduction of deep learning in the DICOM standardCode0
EviPrompt: A Training-Free Evidential Prompt Generation Method for Segment Anything Model in Medical Images—0
Lidar-based Norwegian tree species detection using deep learning—0
Diagonal Hierarchical Consistency Learning for Semi-supervised Medical Image Segmentation—0
Automatic Report Generation for Histopathology images using pre-trained Vision TransformersCode0
Efficient Segmentation with Texture in Ore Images Based on Box-supervised ApproachCode0
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All datasetsADE20KNYU-Depth V2Cityscapes testCityscapes valADE20K valPASCAL ContextS3DIS Area5PASCAL VOC 2012 testS3DISScanNetSUN-RGBDDensePASS

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1InternImage-H (M3I Pre-training)Params (M)1,310—Unverified
2ViT-P (InternImage-H)Validation mIoU63.6—Unverified
3ONE-PEACEValidation mIoU63—Unverified
4InternImage-HValidation mIoU62.9—Unverified
5M3I Pre-training (InternImage-H)Validation mIoU62.9—Unverified
6BEiT-3Validation mIoU62.8—Unverified
7EVAValidation mIoU62.3—Unverified
8ViT-P (OneFormer, InternImage-H)Validation mIoU61.6—Unverified
9ViT-Adapter-L (Mask2Former, BEiTv2 pretrain)Validation mIoU61.5—Unverified
10FD-SwinV2-GValidation mIoU61.4—Unverified