SOTAVerified

Segmentation

Papers

Showing 16011625 of 13072 papers

TitleStatusHype
1st Place Solution of The Robust Vision Challenge 2022 Semantic Segmentation TrackCode1
Valuing Vicinity: Memory attention framework for context-based semantic segmentation in histopathologyCode1
Non-Iterative Scribble-Supervised Learning with Pacing Pseudo-Masks for Medical Image SegmentationCode1
Large-batch Optimization for Dense Visual PredictionsCode1
Cyclical Self-Supervision for Semi-Supervised Ejection Fraction Prediction from Echocardiogram VideosCode1
TIVE: A Toolbox for Identifying Video Instance Segmentation ErrorsCode1
ResAttUNet: Detecting Marine Debris using an Attention activated Residual UNetCode1
Learnable Polyphase Sampling for Shift Invariant and Equivariant Convolutional NetworksCode1
Hierarchical Approach for Joint Semantic, Plant Instance, and Leaf Instance Segmentation in the Agricultural DomainCode1
Exploring Vanilla U-Net for Lesion Segmentation from Whole-body FDG-PET/CT ScansCode1
MOVE: Unsupervised Movable Object Segmentation and DetectionCode1
Exploring Long-Sequence Masked AutoencodersCode1
Feature-Proxy Transformer for Few-Shot SegmentationCode1
LACV-Net: Semantic Segmentation of Large-Scale Point Cloud Scene via Local Adaptive and Comprehensive VLADCode1
AISFormer: Amodal Instance Segmentation with TransformerCode1
CASAPose: Class-Adaptive and Semantic-Aware Multi-Object Pose EstimationCode1
CLIP-Fields: Weakly Supervised Semantic Fields for Robotic MemoryCode1
Semantic Segmentation under Adverse Conditions: A Weather and Nighttime-aware Synthetic Data-based ApproachCode1
Learning Inter-Superpoint Affinity for Weakly Supervised 3D Instance SegmentationCode1
BoxTeacher: Exploring High-Quality Pseudo Labels for Weakly Supervised Instance SegmentationCode1
Global Spectral Filter Memory Network for Video Object SegmentationCode1
OGC: Unsupervised 3D Object Segmentation from Rigid Dynamics of Point CloudsCode1
Training Deep Learning Algorithms on Synthetic Forest Images for Tree DetectionCode1
Automated segmentation and morphological characterization of placental histology images based on a single labeled imageCode1
Humans need not label more humans: Occlusion Copy & Paste for Occluded Human Instance SegmentationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1unSAM+ (Semi-supervised)Average Precision42.8Unverified
2SAMAverage Precision38.9Unverified
#ModelMetricClaimedVerifiedStatus
1HNN10%20Unverified
#ModelMetricClaimedVerifiedStatus
1ABANetF1 Score96.82Unverified
#ModelMetricClaimedVerifiedStatus
1ResNet50 + DeepLabV3+F1 score0.77Unverified
#ModelMetricClaimedVerifiedStatus
1LangGasIoU0.69Unverified