SOTAVerified

Semantic Segmentation

Papers

Showing 851900 of 14763 papers

TitleStatusHype
DA-TransUNet: Integrating Spatial and Channel Dual Attention with Transformer U-Net for Medical Image SegmentationCode1
DB-SAM: Delving into High Quality Universal Medical Image SegmentationCode1
DatasetGAN: Efficient Labeled Data Factory with Minimal Human EffortCode1
Dataset Enhancement with Instance-Level AugmentationsCode1
DC-SAM: In-Context Segment Anything in Images and Videos via Dual ConsistencyCode1
Data-Free Quantization Through Weight Equalization and Bias CorrectionCode1
Bootstrapping Semi-supervised Medical Image Segmentation with Anatomical-aware Contrastive DistillationCode1
Dataset Diffusion: Diffusion-based Synthetic Dataset Generation for Pixel-Level Semantic SegmentationCode1
Bootstrapped Masked Autoencoders for Vision BERT PretrainingCode1
Active Token MixerCode1
BootPIG: Bootstrapping Zero-shot Personalized Image Generation Capabilities in Pretrained Diffusion ModelsCode1
Bootstrapping Objectness from Videos by Relaxed Common Fate and Visual GroupingCode1
DCSAU-Net: A Deeper and More Compact Split-Attention U-Net for Medical Image SegmentationCode1
Boosting Unsupervised Semantic Segmentation with Principal Mask ProposalsCode1
Boosting Semi-supervised Image Segmentation with Global and Local Mutual Information RegularizationCode1
Unified Domain Adaptive Semantic SegmentationCode1
Boosting Semantic Human Matting with Coarse AnnotationsCode1
DAFormer: Improving Network Architectures and Training Strategies for Domain-Adaptive Semantic SegmentationCode1
From Claims to Evidence: A Unified Framework and Critical Analysis of CNN vs. Transformer vs. Mamba in Medical Image SegmentationCode1
A Location-Sensitive Local Prototype Network for Few-Shot Medical Image SegmentationCode1
DAE-Former: Dual Attention-guided Efficient Transformer for Medical Image SegmentationCode1
DANNet: A One-Stage Domain Adaptation Network for Unsupervised Nighttime Semantic SegmentationCode1
Data Augmentation-free Unsupervised Learning for 3D Point Cloud UnderstandingCode1
D3RM: A Discrete Denoising Diffusion Refinement Model for Piano TranscriptionCode1
ALPS: An Auto-Labeling and Pre-training Scheme for Remote Sensing Segmentation With Segment Anything ModelCode1
ALSO: Automotive Lidar Self-supervision by Occupancy estimationCode1
Boosting Semi-Supervised Semantic Segmentation with Probabilistic RepresentationsCode1
Alternate Diverse Teaching for Semi-supervised Medical Image SegmentationCode1
BoMuDANet: Unsupervised Adaptation for Visual Scene Understanding in Unstructured Driving EnvironmentsCode1
1st Place Solution for the 5th LSVOS Challenge: Video Instance SegmentationCode1
Active Negative Loss: A Robust Framework for Learning with Noisy LabelsCode1
Bootstraping Clustering of Gaussians for View-consistent 3D Scene UnderstandingCode1
Active Pointly-Supervised Instance SegmentationCode1
Bootstrapping Semantic Segmentation with Regional ContrastCode1
Boundary-assisted Region Proposal Networks for Nucleus SegmentationCode1
Data Efficient 3D Learner via Knowledge Transferred from 2D ModelCode1
DAAIN: Detection of Anomalous and Adversarial Input using Normalizing FlowsCode1
BlockCopy: High-Resolution Video Processing with Block-Sparse Feature Propagation and Online PoliciesCode1
AME-CAM: Attentive Multiple-Exit CAM for Weakly Supervised Segmentation on MRI Brain TumorCode1
Boundary-aware Contrastive Learning for Semi-supervised Nuclei Instance SegmentationCode1
Boundary-Aware Network for Kidney ParsingCode1
Boundary-Aware Network for Abdominal Multi-Organ SegmentationCode1
BLO-SAM: Bi-level Optimization Based Overfitting-Preventing Finetuning of SAMCode1
Boundary Difference Over Union Loss For Medical Image SegmentationCode1
dacl10k: Benchmark for Semantic Bridge Damage SegmentationCode1
Boundary IoU: Improving Object-Centric Image Segmentation EvaluationCode1
1st Place Solution for the UVO Challenge on Image-based Open-World Segmentation 2021Code1
Amodal Cityscapes: A New Dataset, its Generation, and an Amodal Semantic Segmentation Challenge BaselineCode1
blob loss: instance imbalance aware loss functions for semantic segmentationCode1
Active learning for medical image segmentation with stochastic batchesCode1
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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
4InternImage-HValidation mIoU62.9Unverified
5M3I Pre-training (InternImage-H)Validation 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