SOTAVerified

Semantic Segmentation

Papers

Showing 29262950 of 14763 papers

TitleStatusHype
Continuous Conditional Random Field Convolution for Point Cloud SegmentationCode1
Satellite Image Semantic SegmentationCode1
Vit-GAN: Image-to-image Translation with Vision Transformes and Conditional GANSCode1
Semi-Supervised Semantic Segmentation via Adaptive Equalization LearningCode1
Revitalizing CNN Attentions via Transformers in Self-Supervised Visual Representation LearningCode1
ProgFed: Effective, Communication, and Computation Efficient Federated Learning by Progressive TrainingCode1
BuildingNet: Learning to Label 3D BuildingsCode1
MD Loss: Efficient Training of 3D Seismic Fault Segmentation Network under Sparse Labels by Weakening Anomaly AnnotationCode1
Adaptive Early-Learning Correction for Segmentation from Noisy AnnotationsCode1
E1D3 U-Net for Brain Tumor Segmentation: Submission to the RSNA-ASNR-MICCAI BraTS 2021 ChallengeCode1
Long-tailed Distribution AdaptationCode1
Clustering Plotted Data by Image SegmentationCode1
Shallow Features Guide Unsupervised Domain Adaptation for Semantic Segmentation at Class BoundariesCode1
Self-Supervised Generative Style Transfer for One-Shot Medical Image SegmentationCode1
Transfer Learning U-Net Deep Learning for Lung Ultrasound SegmentationCode1
Transformer Assisted Convolutional Network for Cell Instance SegmentationCode1
Double Encoder-Decoder Networks for Gastrointestinal Polyp SegmentationCode1
Mix3D: Out-of-Context Data Augmentation for 3D ScenesCode1
Pixel-Level Bijective Matching for Video Object SegmentationCode1
Semantic-Guided Zero-Shot Learning for Low-Light Image/Video EnhancementCode1
Learn then Test: Calibrating Predictive Algorithms to Achieve Risk ControlCode1
Bounding Box Tightness Prior for Weakly Supervised Image SegmentationCode1
Instance Segmentation Challenge Track Technical Report, VIPriors Workshop at ICCV 2021: Task-Specific Copy-Paste Data Augmentation Method for Instance SegmentationCode1
NASViT: Neural Architecture Search for Efficient Vision Transformers with Gradient Conflict aware Supernet TrainingCode1
Training on Polar Image Transformations Improves Biomedical Image SegmentationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1InternImage-H (M3I Pre-training)Params (M)1,310Unverified
2ViT-P (InternImage-H)Validation mIoU63.6Unverified
3ONE-PEACEValidation mIoU63Unverified
4M3I Pre-training (InternImage-H)Validation mIoU62.9Unverified
5InternImage-HValidation mIoU62.9Unverified
6BEiT-3Validation mIoU62.8Unverified
7EVAValidation mIoU62.3Unverified
8ViT-P (OneFormer, InternImage-H)Validation mIoU61.6Unverified
9ViT-Adapter-L (Mask2Former, BEiTv2 pretrain)Validation mIoU61.5Unverified
10FD-SwinV2-GValidation mIoU61.4Unverified