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Semantic Segmentation

Papers

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Showing 4801–4825 of 14763 papers

TitleStatusHype
Gazebo Plants: Simulating Plant-Robot Interaction with Cosserat Rods—0
Bayesian image segmentations by Potts prior and loopy belief propagation—0
Actor and Action Modular Network for Text-based Video Segmentation—0
Gaussian Heritage: 3D Digitization of Cultural Heritage with Integrated Object Segmentation—0
Bayesian Generative Models for Knowledge Transfer in MRI Semantic Segmentation Problems—0
Deeply supervised UNet for semantic segmentation to assist dermatopathological assessment of Basal Cell Carcinoma (BCC)—0
Bayesian Federated Neural Matching that Completes Full Information—0
Deeply Self-Supervised Contour Embedded Neural Network Applied to Liver Segmentation—0
Gaussian Filter in CRF Based Semantic Segmentation—0
Gaussian Radar Transformer for Semantic Segmentation in Noisy Radar Data—0
Deeply Learning the Messages in Message Passing Inference—0
Deeply Cascaded U-Net for Multi-Task Image Processing—0
Bayesian Deep Learning for Affordance Segmentation in images—0
Deep LOGISMOS: Deep Learning Graph-based 3D Segmentation of Pancreatic Tumors on CT scans—0
Deep LF-Net: Semantic Lung Segmentation from Indian Chest Radiographs Including Severely Unhealthy Images—0
Bayesian Deep Learning Approaches for Uncertainty-Aware Retinal OCT Image Segmentation for Multiple Sclerosis—0
Ammonia-Net: A Multi-task Joint Learning Model for Multi-class Segmentation and Classification in Tooth-marked Tongue Diagnosis—0
Bayesian Active Contours with Affine-Invariant, Elastic Shape Prior—0
Deep learning with RGB and thermal images onboard a drone for monitoring operations—0
AMLP:Adaptive Masking Lesion Patches for Self-supervised Medical Image Segmentation—0
Deep Learning with Anatomical Priors: Imitating Enhanced Autoencoders in Latent Space for Improved Pelvic Bone Segmentation in MRI—0
Deep Learning Training Procedure Augmentations—0
Region homogeneity in the Logarithmic Image Processing framework: application to region growing algorithms—0
Gaussian Dynamic Convolution for Efficient Single-Image Segmentation—0
Gaze2Segment: A Pilot Study for Integrating Eye-Tracking Technology into Medical Image Segmentation—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
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