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Semantic Segmentation

Papers

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Showing 10276–10300 of 14763 papers

TitleStatusHype
Improving Image co-segmentation via Deep Metric Learning—0
Improving Learning Effectiveness For Object Detection and Classification in Cluttered Backgrounds—0
Improving Lesion Segmentation in Medical Images by Global and Regional Feature Compensation—0
Improving Lidar-Based Semantic Segmentation of Top-View Grid Maps by Learning Features in Complementary Representations—0
Improving Medical Visual Representation Learning with Pathological-level Cross-Modal Alignment and Correlation Exploration—0
Improving Multi-Modal Learning with Uni-Modal Teachers—0
Improving Normalization with the James-Stein Estimator—0
Improving Online Performance Prediction for Semantic Segmentation—0
Improving Open-Set Semantic Segmentation in 3D Point Clouds by Conditional Channel Capacity Maximization: Preliminary Results—0
Improving Pallet Detection Using Synthetic Data—0
Improving Performance of Semantic Segmentation CycleGANs by Noise Injection into the Latent Segmentation Space—0
Improving Pixel-based MIM by Reducing Wasted Modeling Capability—0
Improving Pixel Embedding Learning through Intermediate Distance Regression Supervision for Instance Segmentation—0
Improving Point Cloud Semantic Segmentation by Learning 3D Object Detection—0
Improving Polyphonic Sound Event Detection on Multichannel Recordings with the Sørensen-Dice Coefficient Loss and Transfer Learning—0
Improving Prediction Accuracy of Semantic Segmentation Methods Using Convolutional Autoencoder Based Pre-processing Layers—0
Improving Predictive Performance and Calibration by Weight Fusion in Semantic Segmentation—0
Improving RANSAC-Based Segmentation Through CNN Encapsulation—0
Improving Robustness of Semantic Segmentation to Motion-Blur Using Class-Centric Augmentation—0
Improving Segment Anything on the Fly: Auxiliary Online Learning and Adaptive Fusion for Medical Image Segmentation—0
Improving Semantic Segmentation in Transformers using Hierarchical Inter-Level Attention—0
Improving Semantic Segmentation of Aerial Images Using Patch-based Attention—0
Improving Semantic Segmentation through Spatio-Temporal Consistency Learned from Videos—0
Improving Semantic Segmentation via Dilated Affinity—0
Improving Semantic Segmentation via Self-Training—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