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Human Parsing
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Human parsing is the task of segmenting a human image into different fine-grained semantic parts such as head, torso, arms and legs.
<span style="color:grey; opacity: 0.6">( Image credit: Multi-Human-Parsing (MHP) )</span>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Self-Learning with Rectification Strategy for Human Parsing
Hierarchical Human Parsing with Typed Part-Relation Reasoning
Knowledge Integration Networks for Action Recognition
C-DLinkNet: considering multi-level semantic features for human parsing
Learning Compositional Neural Information Fusion for Human Parsing
Learning Semantic Neural Tree for Human Parsing
Learning from Synthetic Animals
Grapy-ML: Graph Pyramid Mutual Learning for Cross-dataset Human Parsing
Self-Correction for Human Parsing
Beyond Human Parts: Dual Part-Aligned Representations for Person Re-Identification
Cross-Domain Complementary Learning Using Pose for Multi-Person Part Segmentation
Fashion Editing with Adversarial Parsing Learning
Graphonomy: Universal Human Parsing via Graph Transfer Learning
Self-Supervised Learning via Conditional Motion Propagation
Towards Multi-pose Guided Virtual Try-on Network
Capture Dense: Markerless Motion Capture Meets Dense Pose Estimation
Parsing R-CNN for Instance-Level Human Analysis
CCNet: Criss-Cross Attention for Semantic Segmentation
Devil in the Details: Towards Accurate Single and Multiple Human Parsing
Keypoint Based Weakly Supervised Human Parsing
Adaptive Temporal Encoding Network for Video Instance-level Human Parsing
Instance-level Human Parsing via Part Grouping Network
Macro-Micro Adversarial Network for Human Parsing
Weakly and Semi Supervised Human Body Part Parsing via Pose-Guided Knowledge Transfer
Progressive refinement: a method of coarse-to-fine image parsing using stacked network
Understanding Humans in Crowded Scenes: Deep Nested Adversarial Learning and A New Benchmark for Multi-Human Parsing
Look into Person: Joint Body Parsing & Pose Estimation Network and A New Benchmark
Cross-domain Human Parsing via Adversarial Feature and Label Adaptation
Holistic, Instance-Level Human Parsing
Semantic Instance Segmentation with a Discriminative Loss Function
Multiple-Human Parsing in the Wild
Clothing and People - A Social Signal Processing Perspective
Mask R-CNN
Look into Person: Self-supervised Structure-sensitive Learning and A New Benchmark for Human Parsing
Instance-aware Semantic Segmentation via Multi-task Network Cascades
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