https://github.com/CASIA-IVA-Lab/ISP-reID
공식 코드Identity-Guided Human Semantic Parsing for Person Re-Identification
Papers with Code 아카이브
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>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Charleshhy/Grapy-ML
공식 코드Grapy-ML: Graph Pyramid Mutual Learning for Cross-dataset Human Parsing
https://github.com/Charleshhy/One-shot-Human-Parsing
공식 코드https://github.com/Engineering-Course/CIHP_PGN
공식 코드https://github.com/Engineering-Course/LIP_SSL
공식 코드Look into Person: Self-supervised Structure-sensitive Learning and A New Benchmark for Human Parsing
https://github.com/Gait3D/Gait3D-Benchmark
공식 코드Parsing is All You Need for Accurate Gait Recognition in the Wild
https://github.com/Gaoyiminggithub/Graphonomy
공식 코드Graphonomy: Universal Human Parsing via Graph Transfer Learning
https://github.com/Gaoyiminggithub/Graphonomy-Panoptic
공식 코드Graphonomy: Universal Image Parsing via Graph Reasoning and Transfer
https://github.com/HCPLab-SYSU/ATEN
공식 코드Adaptive Temporal Encoding Network for Video Instance-level Human Parsing
https://github.com/JitengMu/Learning-from-Synthetic-Animals
공식 코드https://github.com/KiseKloset/DM-VTON
공식 코드https://github.com/MVIG-SJTU/WSHP
공식 코드Weakly and Semi Supervised Human Body Part Parsing via Pose-Guided Knowledge Transfer
https://github.com/PeikeLi/Self-Correction-Human-Parsing
공식 코드https://github.com/RoyalVane/MMAN
공식 코드https://github.com/XiaohangZhan/conditional-motion-propagation
공식 코드https://github.com/Zhangjinso/PISE
공식 코드https://github.com/ZzzjzzZ/CompositionalHumanParsing
공식 코드Learning Compositional Neural Information Fusion for Human Parsing
https://github.com/cjm-sfw/SMP
공식 코드Single-stage Multi-human Parsing via Point Sets and Center-based Offsets
https://github.com/cjm-sfw/Uniparser
공식 코드UniParser: Multi-Human Parsing with Unified Correlation Representation Learning
https://github.com/envision-research/mtmamba
공식 코드MTMamba: Enhancing Multi-Task Dense Scene Understanding by Mamba-Based Decoders
https://github.com/eth-ait/4d-dress
공식 코드4D-DRESS: A 4D Dataset of Real-world Human Clothing with Semantic Annotations
https://github.com/geyuying/PF-AFN
공식 코드https://github.com/ggjy/P2Net.pytorch
공식 코드Beyond Human Parts: Dual Part-Aligned Representations for Person Re-Identification
https://github.com/hh23333/tsd
공식 코드Part Representation Learning with Teacher-Student Decoder for Occluded Person Re-identification
https://github.com/hlzhu09/Hierarchical-Human-Parsing
공식 코드Hierarchical Human Parsing with Typed Part-Relation Reasoning
https://github.com/hongfz16/hcmoco
공식 코드Versatile Multi-Modal Pre-Training for Human-Centric Perception
https://github.com/kcyt/integratedpifu
공식 코드IntegratedPIFu: Integrated Pixel Aligned Implicit Function for Single-view Human Reconstruction
https://github.com/kevinlin311tw/CDCL-human-part-segmentation
공식 코드Cross-Domain Complementary Learning Using Pose for Multi-Person Part Segmentation
https://github.com/kimbingng/deskpro
공식 코드Identity-Sensitive Knowledge Propagation for Cloth-Changing Person Re-identification
https://github.com/liujf69/EPP-Net-Action
공식 코드https://github.com/liujf69/ipp-net-parsing
공식 코드Integrating Human Parsing and Pose Network for Human Action Recognition
https://github.com/liutinglt/CE2P
공식 코드Devil in the Details: Towards Accurate Single and Multiple Human Parsing
https://github.com/opengvlab/humanbench
공식 코드HumanBench: Towards General Human-centric Perception with Projector Assisted Pretraining
https://github.com/opengvlab/unihcp
공식 코드https://github.com/prismformore/InvPT
공식 코드InvPT: Inverted Pyramid Multi-task Transformer for Dense Scene Understanding
https://github.com/shiqiyu/opengait
공식 코드Exploring More from Multiple Gait Modalities for Human Identification
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.