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Semantic Segmentation

Papers

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Showing 4851–4900 of 14763 papers

TitleStatusHype
Synthetic Poisoning Attacks: The Impact of Poisoned MRI Image on U-Net Brain Tumor Segmentation—0
Gaze-Assisted Human-Centric Domain Adaptation for Cardiac Ultrasound Image Segmentation—0
FE-UNet: Frequency Domain Enhanced U-Net with Segment Anything Capability for Versatile Image Segmentation—0
LeAP: Consistent multi-domain 3D labeling using Foundation Models—0
Disentangling CLIP for Multi-Object Perception—0
DILLEMA: Diffusion and Large Language Models for Multi-Modal AugmentationCode0
Rethinking the Global Knowledge of CLIP in Training-Free Open-Vocabulary Semantic Segmentation—0
ZISVFM: Zero-Shot Object Instance Segmentation in Indoor Robotic Environments with Vision Foundation ModelsCode0
IMDPrompter: Adapting SAM to Image Manipulation Detection by Cross-View Automated Prompt Learning—0
Deep Ensemble approach for Enhancing Brain Tumor Segmentation in Resource-Limited Settings—0
Transfer Risk Map: Mitigating Pixel-level Negative Transfer in Medical Segmentation—0
Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications—0
Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation—0
A Self-Supervised Framework for Improved Generalisability in Ultrasound B-mode Image Segmentation—0
RFMedSAM 2: Automatic Prompt Refinement for Enhanced Volumetric Medical Image Segmentation with SAM 2—0
Memory Efficient Transformer Adapter for Dense Predictions—0
Rethinking Vision Transformer for Object Centric Foundation ModelsCode0
Test Time Training for 4D Medical Image InterpolationCode0
Geometric Framework for Cell Oversegmentation—0
Exploring Few-Shot Defect Segmentation in General Industrial Scenarios with Metric Learning and Vision Foundation ModelsCode0
Distribution-aware Fairness Learning in Medical Image Segmentation From A Control-Theoretic PerspectiveCode0
Self-Prompt SAM: Medical Image Segmentation via Automatic Prompt SAM Adaptation—0
SAM-guided Pseudo Label Enhancement for Multi-modal 3D Semantic Segmentation—0
A Turing Test for Artificial Nets devoted to model Human Vision—0
Entropy-based measure of rock sample heterogeneity derived from micro-CT imagesCode0
CAD: Confidence-Aware Adaptive Displacement for Semi-Supervised Medical Image Segmentation—0
Let Human Sketches Help: Empowering Challenging Image Segmentation Task with Freehand Sketches—0
ContextFormer: Redefining Efficiency in Semantic Segmentation—0
Integrating Semi-Supervised and Active Learning for Semantic Segmentation—0
SynthmanticLiDAR: A Synthetic Dataset for Semantic Segmentation on LiDAR ImagingCode0
From Semantic Segmentation of Natural Images to Medical Image Segmentation Using ViT-Based Architectures—0
Lifting by Gaussians: A Simple, Fast and Flexible Method for 3D Instance Segmentation—0
CerraData-4MM: A multimodal benchmark dataset on Cerrado for land use and land cover classificationCode0
Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks—0
Medical Semantic Segmentation with Diffusion Pretrain—0
INT: Instance-Specific Negative Mining for Task-Generic Promptable Segmentation—0
Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations—0
Ground Awareness in Deep Learning for Large Outdoor Point Cloud Segmentation—0
RUN: Reversible Unfolding Network for Concealed Object Segmentation—0
3DSES: an indoor Lidar point cloud segmentation dataset with real and pseudo-labels from a 3D model—0
Point Cloud Upsampling as Statistical Shape Model for Pelvic—0
Beyond-Labels: Advancing Open-Vocabulary Segmentation With Vision-Language Models—0
Post-Training Quantization for 3D Medical Image Segmentation: A Practical Study on Real Inference EnginesCode0
Efficient Knowledge Distillation of SAM for Medical Image Segmentation—0
AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies—0
The Linear Attention Resurrection in Vision Transformer—0
Cross-Domain Semantic Segmentation with Large Language Model-Assisted Descriptor Generation—0
LSU-Net: Lightweight Automatic Organs Segmentation Network For Medical Images—0
DynAlign: Unsupervised Dynamic Taxonomy Alignment for Cross-Domain Segmentation—0
D-PLS: Decoupled Semantic Segmentation for 4D-Panoptic-LiDAR-Segmentation—0
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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
4M3I Pre-training (InternImage-H)Validation mIoU62.9—Unverified
5InternImage-HValidation 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