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Segmentation

Papers

Showing 176200 of 13072 papers

TitleStatusHype
1st Place Solution for PSG competition with ECCV'22 SenseHuman WorkshopCode2
Fields of The World: A Machine Learning Benchmark Dataset For Global Agricultural Field Boundary SegmentationCode2
FastInst: A Simple Query-Based Model for Real-Time Instance SegmentationCode2
AgileFormer: Spatially Agile Transformer UNet for Medical Image SegmentationCode2
FACT: Frame-Action Cross-Attention Temporal Modeling for Efficient Action SegmentationCode2
Fast Online Object Tracking and Segmentation: A Unifying ApproachCode2
Find Any Part in 3DCode2
EM-Net: Efficient Channel and Frequency Learning with Mamba for 3D Medical Image SegmentationCode2
ESP-MedSAM: Efficient Self-Prompting SAM for Universal Domain-Generalized Medical Image SegmentationCode2
Efficient Video Object Segmentation via Modulated Cross-Attention MemoryCode2
FAMNet: Frequency-aware Matching Network for Cross-domain Few-shot Medical Image SegmentationCode2
ECLIPSE: Efficient Continual Learning in Panoptic Segmentation with Visual Prompt TuningCode2
FastSurfer-HypVINN: Automated sub-segmentation of the hypothalamus and adjacent structures on high-resolutional brain MRICode2
EasyPortrait -- Face Parsing and Portrait Segmentation DatasetCode2
FEC: Fast Euclidean Clustering for Point Cloud SegmentationCode2
Alleviating Textual Reliance in Medical Language-guided Segmentation via Prototype-driven Semantic ApproximationCode2
Ambiguous Medical Image Segmentation using Diffusion ModelsCode2
Focal Modulation NetworksCode2
FOCUS: Towards Universal Foreground SegmentationCode2
Aligning and Prompting Everything All at Once for Universal Visual PerceptionCode2
FreeTumor: Advance Tumor Segmentation via Large-Scale Tumor SynthesisCode2
From SAM to CAMs: Exploring Segment Anything Model for Weakly Supervised Semantic SegmentationCode2
Frozen CLIP: A Strong Backbone for Weakly Supervised Semantic SegmentationCode2
UNetFormer: A UNet-like Transformer for Efficient Semantic Segmentation of Remote Sensing Urban Scene ImageryCode2
A fully automatic AI system for tooth and alveolar bone segmentation from cone-beam CT imagesCode2
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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