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SOTA
Semantische Segmentierung
Semantic Segmentation On Lip Val
Semantic Segmentation On Lip Val
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mIoU
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Columns
Modellname
mIoU
Paper Title
Repository
MuLA (ResNet-101)
49.30%
Mutual Learning to Adapt for Joint Human Parsing and Pose Estimation
-
HRNetV2 (HRNetV2-W48)
55.90%
High-Resolution Representations for Labeling Pixels and Regions
HRNetV2 + OCR + RMI (PaddleClas pretrained)
58.2%
Segmentation Transformer: Object-Contextual Representations for Semantic Segmentation
Attention+SSL (ResNet-101)
44.73%
Look into Person: Self-supervised Structure-sensitive Learning and A New Benchmark for Human Parsing
Hulk(Finetune, ViT-B)
63.98%
Hulk: A Universal Knowledge Translator for Human-Centric Tasks
OCR (ResNet-101)
55.6%
Segmentation Transformer: Object-Contextual Representations for Semantic Segmentation
JPPNet (ResNet-101)
51.37%
Look into Person: Joint Body Parsing & Pose Estimation Network and A New Benchmark
UniHCP (finetune)
63.86%
UniHCP: A Unified Model for Human-Centric Perceptions
MMAN (ResNet-101)
46.81%
Macro-Micro Adversarial Network for Human Parsing
CE2P (ResNet-101)
53.10%
Devil in the Details: Towards Accurate Single and Multiple Human Parsing
OCR (HRNetV2-W48)
56.65%
Segmentation Transformer: Object-Contextual Representations for Semantic Segmentation
SOLIDER
60.50%
Beyond Appearance: a Semantic Controllable Self-Supervised Learning Framework for Human-Centric Visual Tasks
Hulk(Finetune, ViT-L)
66.02%
Hulk: A Universal Knowledge Translator for Human-Centric Tasks
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