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Semantic Segmentation

Papers

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Showing 9776–9800 of 14763 papers

TitleStatusHype
RAD-DINO: Exploring Scalable Medical Image Encoders Beyond Text Supervision—0
USE: Universal Segment Embeddings for Open-Vocabulary Image Segmentation—0
Radar Instance Transformer: Reliable Moving Instance Segmentation in Sparse Radar Point Clouds—0
MSE-Nets: Multi-annotated Semi-supervised Ensemble Networks for Improving Segmentation of Medical Image with Ambiguous Boundaries—0
Using CNNs For Users Segmentation In Video See-Through Augmented Virtuality—0
MSE Loss with Outlying Label for Imbalanced Classification—0
Best Practices in Active Learning for Semantic Segmentation—0
Revisiting Dilated Convolution: A Simple Approach for Weakly- and Semi-Supervised Semantic Segmentation—0
Revisiting Dilated Convolution: A Simple Approach for Weakly- and Semi- Supervised Semantic Segmentation—0
Using Deep Learning to Count Albatrosses from Space—0
Using depth information and colour space variations for improving outdoor robustness for instance segmentation of cabbage—0
R2U++: A Multiscale Recurrent Residual U-Net with Dense Skip Connections for Medical Image Segmentation—0
Revisiting Graph Construction for Fast Image Segmentation—0
Revisiting Image Reconstruction for Semi-supervised Semantic Segmentation—0
Revisiting MAE pre-training for 3D medical image segmentation—0
Revisiting Multi-modal 3D Semantic Segmentation in Real-world Autonomous Driving—0
Revisiting Multi-Scale Feature Fusion for Semantic Segmentation—0
Revisiting Near/Remote Sensing with Geospatial Attention—0
MSDU-net: A Multi-Scale Dilated U-net for Blur Detection—0
A Simple Non-i.i.d. Sampling Approach for Efficient Training and Better Generalization—0
Using Diffusion Priors for Video Amodal Segmentation—0
Revisiting Rubik's Cube: Self-supervised Learning with Volume-wise Transformation for 3D Medical Image Segmentation—0
MS-DCANet: A Novel Segmentation Network For Multi-Modality COVID-19 Medical Images—0
Revisiting Superpixels for Active Learning in Semantic Segmentation With Realistic Annotation Costs—0
R2U3D: Recurrent Residual 3D U-Net for Lung 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