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Semantic Segmentation

Papers

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Showing 11551–11600 of 14763 papers

TitleStatusHype
Translational Symmetry-Aware Facade Parsing for 3D Building Reconstruction—0
TransMedSeg: A Transferable Semantic Framework for Semi-Supervised Medical Image Segmentation—0
Transparency Distortion Robustness for SOTA Image Segmentation Tasks—0
TransUPR: A Transformer-based Uncertain Point Refiner for LiDAR Point Cloud Semantic Segmentation—0
TrashCan: A Semantically-Segmented Dataset towards Visual Detection of Marine Debris—0
Treating Pseudo-labels Generation as Image Matting for Weakly Supervised Semantic Segmentation—0
Tree-Cut for Probabilistic Image Segmentation—0
Tree Instance Segmentation With Temporal Contour Graph—0
Tree level change detection over Ahmedabad city using very high resolution satellite images and Deep Learning—0
TreeNet: A lightweight One-Shot Aggregation Convolutional Network—0
Tree-NET: Enhancing Medical Image Segmentation Through Efficient Low-Level Feature Training—0
TreeSegNet: Adaptive Tree CNNs for Subdecimeter Aerial Image Segmentation—0
Tree semantic segmentation from aerial image time series—0
TrickVOS: A Bag of Tricks for Video Object Segmentation—0
TricycleGAN: Unsupervised Image Synthesis and Segmentation Based on Shape Priors—0
Trilateral Attention Network for Real-time Medical Image Segmentation—0
Trinity: A No-Code AI platform for complex spatial datasets—0
Tri-Plane Mamba: Efficiently Adapting Segment Anything Model for 3D Medical Images—0
MetricUNet: Synergistic Image- and Voxel-Level Learning for Precise CT Prostate Segmentation via Online Sampling—0
Triple-View Knowledge Distillation for Semi-Supervised Semantic Segmentation—0
Triply Supervised Decoder Networks for Joint Detection and Segmentation—0
Tropical and Extratropical Cyclone Detection Using Deep Learning—0
TRT-ViT: TensorRT-oriented Vision Transformer—0
TrueDeep: A systematic approach of crack detection with less data—0
Trust, but Verify: Robust Image Segmentation using Deep Learning—0
TRUSTED: The Paired 3D Transabdominal Ultrasound and CT Human Data for Kidney Segmentation and Registration Research—0
Trusting Semantic Segmentation Networks—0
Trustworthy Deep Learning for Medical Image Segmentation—0
SUPER-Net: Trustworthy Medical Image Segmentation with Uncertainty Propagation in Encoder-Decoder Networks—0
TS40K: a 3D Point Cloud Dataset of Rural Terrain and Electrical Transmission System—0
Tsanet: Temporal and Scale Alignment for Unsupervised Video Object Segmentation—0
TSDASeg: A Two-Stage Model with Direct Alignment for Interactive Point Cloud Segmentation—0
TSI-Net: A Timing Sequence Image Segmentation Network for Intracranial Artery Segmentation in Digital Subtraction Angiography—0
TSRFormer: Table Structure Recognition with Transformers—0
TSUBF-Net: Trans-Spatial UNet-like Network with Bi-direction Fusion for Segmentation of Adenoid Hypertrophy in CT—0
TTT-KD: Test-Time Training for 3D Semantic Segmentation through Knowledge Distillation from Foundation Models—0
Tubular Shape Aware Data Generation for Semantic Segmentation in Medical Imaging—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
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
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
Two Approaches to Supervised Image Segmentation—0
Two Decades of Colorization and Decolorization for Images and Videos—0
Two-Dimensional Quantum Material Identification via Self-Attention and Soft-labeling in Deep Learning—0
Two layer Ensemble of Deep Learning Models for 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
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