https://github.com/Dacun/Text-based-Person-Search
공식 코드Text-based Person Search in Full Images via Semantic-Driven Proposal Generation
Papers with Code 아카이브
Text based Person Retrieval
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Delong-liu-bupt/Word4Per
공식 코드Automatic Synthetic Data and Fine-grained Adaptive Feature Alignment for Composed Person Retrieval
https://github.com/Jarr0d/ViTAA
공식 코드ViTAA: Visual-Textual Attributes Alignment in Person Search by Natural Language
https://github.com/Liu-Yating/CSKT
공식 코드CLIP-based Synergistic Knowledge Transfer for Text-based Person Retrieval
https://github.com/OrangeYHChen/TIPCB
공식 코드TIPCB: A Simple but Effective Part-based Convolutional Baseline for Text-based Person Search
https://github.com/QinYang79/RDE
공식 코드Noisy-Correspondence Learning for Text-to-Image Person Re-identification
https://github.com/Shuyu-XJTU/APTM
공식 코드https://github.com/TencentYoutuResearch/PersonReID-NAFS
공식 코드Contextual Non-Local Alignment over Full-Scale Representation for Text-Based Person Search
https://github.com/anosorae/irra
공식 코드Cross-Modal Implicit Relation Reasoning and Aligning for Text-to-Image Person Retrieval
https://github.com/brandonhanx/textreid
공식 코드https://github.com/ergastialex/mars
공식 코드MARS: Paying more attention to visual attributes for text-based person search
https://github.com/flame-chasers/rasa
공식 코드RaSa: Relation and Sensitivity Aware Representation Learning for Text-based Person Search
https://github.com/flame-chasers/syntbpr
공식 코드An Empirical Study of Validating Synthetic Data for Text-Based Person Retrieval
https://github.com/flame-chasers/tbps-clip
공식 코드https://github.com/huyquoctrinh/pgds
공식 코드PGDS: Pose-Guidance Deep Supervision for Mitigating Clothes-Changing in Person Re-Identification
https://github.com/huyquoctrinh/pgs
공식 코드PGDS: Pose-Guidance Deep Supervision for Mitigating Clothes-Changing in Person Re-Identification
https://github.com/jahawn-wen/camel-reid
공식 코드CAMeL: Cross-modality Adaptive Meta-Learning for Text-based Person Retrieval
https://github.com/layumi/Image-Text-Embedding
공식 코드Dual-Path Convolutional Image-Text Embeddings with Instance Loss
https://github.com/liu-yating/up-person
공식 코드UP-Person: Unified Parameter-Efficient Transfer Learning for Text-based Person Retrieval
https://github.com/njtechcvlab/rstpreid-dataset
공식 코드DSSL: Deep Surroundings-person Separation Learning for Text-based Person Retrieval
https://github.com/reallsp/SAF
공식 코드Learning Semantic-Aligned Feature Representation for Text-based Person Search
https://github.com/shuanglinyan/CFine
공식 코드CLIP-Driven Fine-grained Text-Image Person Re-identification
https://github.com/tencentyouturesearch/personretrieval-ivt
공식 코드See Finer, See More: Implicit Modality Alignment for Text-based Person Retrieval
https://github.com/zhiyinshao-h/lgur
공식 코드Learning Granularity-Unified Representations for Text-to-Image Person Re-identification
https://github.com/zifyloo/SSAN
공식 코드Semantically Self-Aligned Network for Text-to-Image Part-aware Person Re-identification
https://github.com/zplusdragon/plip
공식 코드PLIP: Language-Image Pre-training for Person Representation Learning
https://github.com/zplusdragon/ufinebench
공식 코드UFineBench: Towards Text-based Person Retrieval with Ultra-fine Granularity
https://github.com/Galaxfy/ReID-test1
Learning Granularity-Unified Representations for Text-to-Image Person Re-identification
https://github.com/JT-Sun/Filtering-WoRA
From Data Deluge to Data Curation: A Filtering-WoRA Paradigm for Efficient Text-based Person Search
https://github.com/Jarr0d/Human-Parsing-Network
ViTAA: Visual-Textual Attributes Alignment in Person Search by Natural Language
https://github.com/ShuangLI59/Person-Search-with-Natural-Language-Description
https://github.com/Suo-Wei/SRCF
https://github.com/TencentYoutuResearch/PersonReID-CACENET
Contextual Non-Local Alignment over Full-Scale Representation for Text-Based Person Search
https://github.com/YingZhangDUT/Cross-Modal-Projection-Learning
https://github.com/pshroff04/Dual_Path_CNN
Dual-Path Convolutional Image-Text Embeddings with Instance Loss
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.