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Semantic Segmentation

Papers

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Showing 10001–10050 of 14763 papers

TitleStatusHype
Pixel-level Encoding and Depth Layering for Instance-level Semantic Labeling—0
Pixel-Level Equalized Matching for Video Object Segmentation—0
Pixel-level Intra-domain Adaptation for Semantic Segmentation—0
Pixel-Level Matching for Video Object Segmentation using Convolutional Neural Networks—0
Pixel-level Semantics Guided Image Colorization—0
PixelNet: Towards a General Pixel-level Architecture—0
Pixel Objectness: Learning to Segment Generic Objects Automatically in Images and Videos—0
Pixel Relationships-based Regularizer for Retinal Vessel Image Segmentation—0
Pixel-wise Modulated Dice Loss for Medical Image Segmentation—0
Pixel-wise object tracking—0
Planar Ultrametric Rounding for Image Segmentation—0
Planar Ultrametrics for Image Segmentation—0
Planecell: Representing the 3D Space with Planes—0
PlaneSAM: Multimodal Plane Instance Segmentation Using the Segment Anything Model—0
PlaneSegNet: Fast and Robust Plane Estimation Using a Single-stage Instance Segmentation CNN—0
PLANesT-3D: A new annotated dataset for segmentation of 3D plant point clouds—0
PlaNet-S: Automatic Semantic Segmentation of Placenta—0
Plant detection from ultra high resolution remote sensing images: A Semantic Segmentation approach based on fuzzy loss—0
Plant Doctor: A hybrid machine learning and image segmentation software to quantify plant damage in video footage—0
Plants Don't Walk on the Street: Common-Sense Reasoning for Reliable Semantic Segmentation—0
Improving segmentation of calcified and non-calcified plaques on CCTA-CPR scans via masking of the artery wall—0
PlasmoID: A dataset for Indonesian malaria parasite detection and segmentation in thin blood smear—0
Platelet enumeration in dense aggregates—0
PlateSegFL: A Privacy-Preserving License Plate Detection Using Federated Segmentation Learning—0
Play and Learn: Using Video Games to Train Computer Vision Models—0
Playing for Benchmarks—0
PLGAN: Generative Adversarial Networks for Power-Line Segmentation in Aerial Images—0
PL-Net: Progressive Learning Network for Medical Image Segmentation—0
PLOP: Probabilistic poLynomial Objects trajectory Planning for autonomous driving—0
PLU-Net: Extraction of multi-scale feature fusion—0
PlutoNet: An Efficient Polyp Segmentation Network with Modified Partial Decoder and Decoder Consistency Training—0
PLUTO: Pathology-Universal Transformer—0
PMODE: Prototypical Mask based Object Dimension Estimation—0
PMR-Net: Parallel Multi-Resolution Encoder-Decoder Network Framework for Medical Image Segmentation—0
PM-VIS: High-Performance Box-Supervised Video Instance Segmentation—0
PMVOS: Pixel-Level Matching-Based Video Object Segmentation—0
Pneumothorax Segmentation: Deep Learning Image Segmentation to predict Pneumothorax—0
PNM: Pixel Null Model for General Image Segmentation—0
P-NOC: adversarial training of CAM generating networks for robust weakly supervised semantic segmentation priors—0
Point2CAD: Reverse Engineering CAD Models from 3D Point Clouds—0
Point2Mask: A Weakly Supervised Approach for Cell Segmentation Using Point Annotation—0
Point2Tree(P2T) -- framework for parameter tuning of semantic and instance segmentation used with mobile laser scanning data in coniferous forest—0
Point Attention Network for Semantic Segmentation of 3D Point Clouds—0
PointAugmenting: Cross-Modal Augmentation for 3D Object Detection—0
Point Cloud Based Scene Segmentation: A Survey—0
Point Cloud Data Simulation and Modelling with Aize Workspace—0
Point Cloud Instance Segmentation using Probabilistic Embeddings—0
Point Cloud Learning with Transformer—0
Point Cloud Scene Completion with Joint Color and Semantic Estimation from Single RGB-D Image—0
Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting—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