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Semantic Segmentation

Papers

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Showing 10151–10200 of 14763 papers

TitleStatusHype
Probabilistic Modeling of Inter- and Intra-observer Variability in Medical Image Segmentation—0
Probabilistic Semantic Mapping for Urban Autonomous Driving Applications—0
Probabilistic Semantic Segmentation Refinement by Monte Carlo Region Growing—0
Probabilistic U-Net with Kendall Shape Spaces for Geometry-Aware Segmentations of Images—0
Probing neural representations of scene perception in a hippocampally dependent task using artificial neural networks—0
Procedural Modeling and Physically Based Rendering for Synthetic Data Generation in Automotive Applications—0
Process-aware and high-fidelity microstructure generation using stable diffusion—0
Progressive Adversarial Semantic Segmentation—0
Progressive Fine-to-Coarse Reconstruction for Accurate Low-Bit Post-Training Quantization in Vision Transformers—0
Progressive Learning with Cross-Window Consistency for Semi-Supervised Semantic Segmentation—0
Progressively Diffused Networks for Semantic Image Segmentation—0
Progressively Dual Prior Guided Few-shot Semantic Segmentation—0
Progressively Growing Generative Adversarial Networks for High Resolution Semantic Segmentation of Satellite Images—0
Generalized Coarse-to-Fine Visual Recognition with Progressive Training—0
Progressive refinement: a method of coarse-to-fine image parsing using stacked network—0
Progressive Vision-Language Prompt for Multi-Organ Multi-Class Cell Semantic Segmentation with Single Branch—0
Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks—0
Projective Skip-Connections for Segmentation Along a Subset of Dimensions in Retinal OCT—0
ProKAN: Progressive Stacking of Kolmogorov-Arnold Networks for Efficient Liver Segmentation—0
ProMamba: Prompt-Mamba for polyp segmentation—0
ProMerge: Prompt and Merge for Unsupervised Instance Segmentation—0
Promoting Segment Anything Model towards Highly Accurate Dichotomous Image Segmentation—0
Prompt2SegCXR:Prompt to Segment All Organs and Diseases in Chest X-rays—0
Prompt-Based Segmentation at Multiple Resolutions and Lighting Conditions using Segment Anything Model 2—0
Prompt-Based Tuning of Transformer Models for Multi-Center Medical Image Segmentation of Head and Neck Cancer—0
Prompt Categories Cluster for Weakly Supervised Semantic Segmentation—0
Prompt-Driven Referring Image Segmentation with Instance Contrasting—0
Prompt Engineering in Segment Anything Model: Methodologies, Applications, and Emerging Challenges—0
CtxMIM: Context-Enhanced Masked Image Modeling for Remote Sensing Image Understanding—0
Prompt-Guided Dual-Path UNet with Mamba for Medical Image Segmentation—0
Prompt-Matched Semantic Segmentation—0
Prompt What You Need: Enhancing Segmentation in Rainy Scenes with Anchor-based Prompting—0
Propagating Semantic Labels in Video Data—0
Proposal-free Lidar Panoptic Segmentation with Pillar-level Affinity—0
Proposal-free Network for Instance-level Object Segmentation—0
Proposal-Free Volumetric Instance Segmentation from Latent Single-Instance Masks—0
PAM: A Propagation-Based Model for Segmenting Any 3D Objects across Multi-Modal Medical Images—0
ProSAM: Enhancing the Robustness of SAM-based Visual Reference Segmentation with Probabilistic Prompts—0
Prostate Cancer Semantic Segmentation by Gleason Score Group in bi-parametric MRI with Self Attention Model on the Peripheral Zone—0
Prostate Segmentation using 2D Bridged U-net—0
Protecting Semantic Segmentation Models by Using Block-wise Image Encryption with Secret Key from Unauthorized Access—0
ProtoGMM: Multi-prototype Gaussian-Mixture-based Domain Adaptation Model for Semantic Segmentation—0
ProtoGuard-guided PROPEL: Class-Aware Prototype Enhancement and Progressive Labeling for Incremental 3D Point Cloud Segmentation—0
ProtoSeg: A Prototype-Based Point Cloud Instance Segmentation Method—0
ProtoTransfer: Cross-Modal Prototype Transfer for Point Cloud Segmentation—0
PROTOTYPE-ASSISTED ADVERSARIAL LEARNING FOR UNSUPERVISED DOMAIN ADAPTATION—0
Prototype-Based Approach for One-Shot Segmentation of Brain Tumors using Few-Shot Learning—0
Prototype-Based Image Prompting for Weakly Supervised Histopathological Image Segmentation—0
Prototype Correlation Matching and Class-Relation Reasoning for Few-Shot Medical Image Segmentation—0
Prototype Guided Federated Learning of Visual Feature Representations—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
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