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Semantic Segmentation

Papers

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Showing 10226–10250 of 14763 papers

TitleStatusHype
IMP: Instance Mask Projection for High Accuracy Semantic Segmentation of Things—0
Implanting Synthetic Lesions for Improving Liver Lesion Segmentation in CT Exams—0
Implementation of a Modified U-Net for Medical Image Segmentation on Edge Devices—0
Implementation of improved RGBD 3D target detection model based on FPGA heterogeneous computing architecture—0
Implicit and Explicit Language Guidance for Diffusion-based Visual Perception—0
Implicit Label Augmentation on Partially Annotated Clips via Temporally-Adaptive Features Learning—0
Implicit Modeling -- A Generalization of Discriminative and Generative Approaches—0
Implicit Ray-Transformers for Multi-view Remote Sensing Image Segmentation—0
Implicit Surface Contrastive Clustering for LiDAR Point Clouds—0
Implicit U-KAN2.0: Dynamic, Efficient and Interpretable Medical Image Segmentation—0
Implicit U-Net for volumetric medical image segmentation—0
Importance-Aware Image Segmentation-based Semantic Communication for Autonomous Driving—0
Importance-Aware Semantic Segmentation in Self-Driving with Discrete Wasserstein Training—0
Importance of Image Enhancement Techniques in Color Image Segmentation: A Comprehensive and Comparative Study—0
Importance of Self-Consistency in Active Learning for Semantic Segmentation—0
Improved Block Merging for 3D Point Cloud Instance Segmentation—0
Improved Crop and Weed Detection with Diverse Data Ensemble Learning—0
Improved-Flow Warp Module for Remote Sensing Semantic Segmentation—0
Improved Inference via Deep Input Transfer—0
Improved LiDAR Odometry and Mapping using Deep Semantic Segmentation and Novel Outliers Detection—0
Improved-Mask R-CNN: Towards an Accurate Generic MSK MRI instance segmentation platform (Data from the Osteoarthritis Initiative)—0
Improved Noise and Attack Robustness for Semantic Segmentation by Using Multi-Task Training with Self-Supervised Depth Estimation—0
Improved Real-Time Monocular SLAM Using Semantic Segmentation on Selective Frames—0
Improved Training for Self-Training by Confidence Assessments—0
Improved Unet brain tumor image segmentation based on GSConv module and ECA attention mechanism—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