SOTAVerified

Semantic Segmentation

Papers

Showing 52015225 of 14763 papers

TitleStatusHype
MCDAL: Maximum Classifier Discrepancy for Active LearningCode0
MCDS-VSS: Moving Camera Dynamic Scene Video Semantic Segmentation by Filtering with Self-Supervised Geometry and MotionCode0
MCA: Moment Channel Attention NetworksCode0
MCU-Net: A framework towards uncertainty representations for decision support system patient referrals in healthcare contextsCode0
MedCL: Learning Consistent Anatomy Distribution for Scribble-supervised Medical Image SegmentationCode0
Compact Bilinear PoolingCode0
A Semi-Automated Usability Evaluation Framework for Interactive Image Segmentation SystemsCode0
Common3D: Self-Supervised Learning of 3D Morphable Models for Common Objects in Neural Feature SpaceCode0
Adversarial Robustness Analysis of Vision-Language Models in Medical Image SegmentationCode0
Accurate Fine-grained Layout Analysis for the Historical Tibetan Document Based on the Instance SegmentationCode0
MAVNet: an Effective Semantic Segmentation Micro-Network for MAV-based TasksCode0
Combo Loss: Handling Input and Output Imbalance in Multi-Organ SegmentationCode0
CDRNet: Accurate Cup-to-Disc Ratio Measurement with Tight Bounding Box Supervision in Fundus Photography Using Deep LearningCode0
Matterport3D: Learning from RGB-D Data in Indoor EnvironmentsCode0
Combining UPerNet and ConvNeXt for Contrails Identification to reduce Global WarmingCode0
A Robotics-Inspired Scanpath Model Reveals the Importance of Uncertainty and Semantic Object Cues for Gaze Guidance in Dynamic ScenesCode0
Maturity-Aware Active Learning for Semantic Segmentation with Hierarchically-Adaptive Sample AssessmentCode0
MBIS: Multivariate Bayesian Image Segmentation ToolCode0
Combining Photogrammetric Computer Vision and Semantic Segmentation for Fine-grained Understanding of Coral Reef Growth under Climate ChangeCode0
MASNet: A Robust Deep Marine Animal Segmentation NetworkCode0
MASSeg : 2nd Technical Report for 4th PVUW MOSE TrackCode0
Mask TextSpotter: An End-to-End Trainable Neural Network for Spotting Text with Arbitrary ShapesCode0
Mask TextSpotter: An End-to-End Trainable Neural Network for Spotting Text with Arbitrary ShapesCode0
Combining Geometric and Topological Information for Boundary EstimationCode0
Combining Fully Convolutional and Recurrent Neural Networks for 3D Biomedical Image SegmentationCode0
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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