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Semantic Segmentation

Papers

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Showing 10201–10250 of 14763 papers

TitleStatusHype
Prototype Guided Network for Anomaly Segmentation—0
Prototype Refinement Network for Few-Shot Segmentation—0
Prototypical Kernel Learning and Open-set Foreground Perception for Generalized Few-shot Semantic Segmentation—0
Prototypical Matching and Open Set Rejection for Zero-Shot Semantic Segmentation—0
Pro-tuning: Unified Prompt Tuning for Vision Tasks—0
PrPSeg: Universal Proposition Learning for Panoramic Renal Pathology Segmentation—0
PRSeg: A Lightweight Patch Rotate MLP Decoder for Semantic Segmentation—0
PRS-Med: Position Reasoning Segmentation with Vision-Language Model in Medical Imaging—0
Pruning Parameterization With Bi-Level Optimization for Efficient Semantic Segmentation on the Edge—0
Pruning random resistive memory for optimizing analogue AI—0
Pseudo-Boolean Polynomials Approach To Edge Detection And Image Segmentation—0
PseudoClick: Interactive Image Segmentation with Click Imitation—0
Pseudo Label-Guided Multi Task Learning for Scene Understanding—0
Pseudo Labelling for Enhanced Masked Autoencoders—0
Pseudo Mask Augmented Object Detection—0
Pseudo Pixel-level Labeling for Images with Evolving Content—0
PSGformer: Enhancing 3D Point Cloud Instance Segmentation via Precise Semantic Guidance—0
PSO-UNet: Particle Swarm-Optimized U-Net Framework for Precise Multimodal Brain Tumor Segmentation—0
PST: Plant segmentation transformer for 3D point clouds of rapeseed plants at the podding stage—0
PTR: A Benchmark for Part-based Conceptual, Relational, and Physical Reasoning—0
PT-ResNet: Perspective Transformation-Based Residual Network for Semantic Road Image Segmentation—0
Pubic Symphysis-Fetal Head Segmentation Network Using BiFormer Attention Mechanism and Multipath Dilated Convolution—0
Pulling Things out of Perspective—0
Pull the Plug? Predicting If Computers or Humans Should Segment Images—0
PuppeteerGAN: Arbitrary Portrait Animation With Semantic-Aware Appearance Transformation—0
PUPS: Point Cloud Unified Panoptic Segmentation—0
Pushing the Boundaries of Boundary Detection using Deep Learning—0
Pushing the Limits of Radiology with Joint Modeling of Visual and Textual Information—0
Push the Boundary of SAM: A Pseudo-label Correction Framework for Medical Segmentation—0
Putting 3D Spatially Sparse Networks on a Diet—0
PV-RCNN++: Semantical Point-Voxel Feature Interaction for 3D Object Detection—0
PVUW 2025 Challenge Report: Advances in Pixel-level Understanding of Complex Videos in the Wild—0
Pylon Model for Semantic Segmentation—0
Pyramid Architecture for Multi-Scale Processing in Point Cloud Segmentation—0
Pyramid Attention Network for Semantic Segmentation—0
Pyramid Dilated Deeper ConvLSTM for Video Salient Object Detection—0
Pyramid Fusion Transformer for Semantic Segmentation—0
Pyramid Graph Networks With Connection Attentions for Region-Based One-Shot Semantic Segmentation—0
Pyramid Medical Transformer for Medical Image Segmentation—0
Pyramid Point: A Multi-Level Focusing Network for Revisiting Feature Layers—0
PyramNet: Point Cloud Pyramid Attention Network and Graph Embedding Module for Classification and Segmentation—0
Q2A: Querying Implicit Fully Continuous Feature Pyramid to Align Features for Medical Image Segmentation—0
QIS : Interactive Segmentation via Quasi-Conformal Mappings—0
Q-learning optimization in a multi-agents system for image segmentation—0
Q-Segment: Segmenting Images In-Sensor for Vessel-Based Medical Diagnosis—0
QuadFormer: Quadruple Transformer for Unsupervised Domain Adaptation in Power Line Segmentation of Aerial Images—0
Quadruple Augmented Pyramid Network for Multi-class COVID-19 Segmentation via CT—0
Quality-Adaptive Split-Federated Learning for Segmenting Medical Images with Inaccurate Annotations—0
Quality-aware semi-supervised learning for CMR segmentation—0
Automatic quality control framework for more reliable integration of machine learning-based image segmentation into medical workflows—0
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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
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