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Semantic Segmentation

Papers

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Showing 9076–9100 of 14763 papers

TitleStatusHype
TSUBF-Net: Trans-Spatial UNet-like Network with Bi-direction Fusion for Segmentation of Adenoid Hypertrophy in CT—0
MultiTask-CenterNet (MCN): Efficient and Diverse Multitask Learning using an Anchor Free Approach—0
Multi-Target Domain Adaptation with Collaborative Consistency Learning—0
CANet: Channel Extending and Axial Attention Catching Network for Multi-structure Kidney Segmentation—0
TTT-KD: Test-Time Training for 3D Semantic Segmentation through Knowledge Distillation from Foundation Models—0
Method of detecting the defects of the end face of steel coils—0
Multi-stream CNN based Video Semantic Segmentation for Automated Driving—0
Multi-stream 3D FCN with Multi-scale Deep Supervision for Multi-modality Isointense Infant Brain MR Image Segmentation—0
Tubular Shape Aware Data Generation for Semantic Segmentation in Medical Imaging—0
What Can be Seen is What You Get: Structure Aware Point Cloud Augmentation—0
Multi-Stain Multi-Level Convolutional Network for Multi-Tissue Breast Cancer Image Segmentation—0
TUM2TWIN: Introducing the Large-Scale Multimodal Urban Digital Twin Benchmark Dataset—0
Tumor-Centered Patching for Enhanced Medical Image Segmentation—0
Tumor segmentation on whole slide images: training or prompting?—0
Multi-Stage Pathological Image Classification using Semantic Segmentation—0
TuNet: End-to-end Hierarchical Brain Tumor Segmentation using Cascaded Networks—0
Tuning a SAM-Based Model with Multi-Cognitive Visual Adapter to Remote Sensing Instance Segmentation—0
Tuning-free Universally-Supervised Semantic Segmentation—0
Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations—0
Multi-stage Object Detection with Group Recursive Learning—0
What Can Be Transferred: Unsupervised Domain Adaptation for Endoscopic Lesions Segmentation—0
TWIG: Two-Step Image Generation using Segmentation Masks in Diffusion Models—0
Twin Deformable Point Convolutions for Point Cloud Semantic Segmentation in Remote Sensing Scenes—0
Multi-Stage Fusion for One-Click Segmentation—0
Progressive Curriculum Learning with Scale-Enhanced U-Net for Continuous Airway 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
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