SOTAVerified

Semantic Segmentation

Papers

Showing 33263350 of 14763 papers

TitleStatusHype
Low Latency Instance Segmentation by Continuous Clustering for LiDAR SensorsCode1
Look-into-Object: Self-supervised Structure Modeling for Object RecognitionCode1
Looking Outside the Window: Wide-Context Transformer for the Semantic Segmentation of High-Resolution Remote Sensing ImagesCode1
Evaluation of Segment Anything Model 2: The Role of SAM2 in the Underwater EnvironmentCode1
Improving Segmentation of Objects with Varying Sizes in Biomedical Images using Instance-wise and Center-of-Instance Segmentation Loss FunctionCode1
LoSh: Long-Short Text Joint Prediction Network for Referring Video Object SegmentationCode1
Dataset Diffusion: Diffusion-based Synthetic Dataset Generation for Pixel-Level Semantic SegmentationCode1
DeepSatData: Building large scale datasets of satellite images for training machine learning modelsCode1
UniDA3D: Unified Domain Adaptive 3D Semantic Segmentation PipelineCode1
Look Closer to Segment Better: Boundary Patch Refinement for Instance SegmentationCode1
DatasetGAN: Efficient Labeled Data Factory with Minimal Human EffortCode1
Loss Functions in the Era of Semantic Segmentation: A Survey and OutlookCode1
Improving Sketch Colorization using Adversarial Segmentation ConsistencyCode1
Improving Stain Invariance of CNNs for Segmentation by Fusing Channel Attention and Domain-Adversarial TrainingCode1
DA-TransUNet: Integrating Spatial and Channel Dual Attention with Transformer U-Net for Medical Image SegmentationCode1
Low-Resolution Self-Attention for Semantic SegmentationCode1
Improving the Detection of Small Oriented Objects in Aerial ImagesCode1
BT-Unet: A self-supervised learning framework for biomedical image segmentation using Barlow Twins with U-Net modelsCode1
Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal EffectCode1
BSNet: Box-Supervised Simulation-assisted Mean Teacher for 3D Instance SegmentationCode1
Sam2Rad: A Segmentation Model for Medical Images with Learnable PromptsCode1
Learning with Unmasked Tokens Drives Stronger Vision LearnersCode1
ALGM: Adaptive Local-then-Global Token Merging for Efficient Semantic Segmentation with Plain Vision TransformersCode1
DB-SAM: Delving into High Quality Universal Medical Image SegmentationCode1
Long-tail Detection with Effective Class-MarginsCode1
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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