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Text Matching
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Matching a target text to a source text based on their meaning.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/BangLiu/ArticlePairMatching
공식 코드Matching Article Pairs with Graphical Decomposition and Convolutions
https://github.com/BruceW91/CVSE
공식 코드Consensus-Aware Visual-Semantic Embedding for Image-Text Matching
https://github.com/CPJKU/DeepGenIR
공식 코드A Modern Perspective on Query Likelihood with Deep Generative Retrieval Models
https://github.com/ChenRocks/UNITER
공식 코드https://github.com/CrossmodalGroup/GSMN
공식 코드https://github.com/Erutan-pku/LCN-for-Chinese-QA
공식 코드https://github.com/FingerRec/OA-Transformer
공식 코드https://github.com/HaoYang0123/Position-Focused-Attention-Network
공식 코드https://github.com/HongyuGong/Document-Similarity-via-Hidden-Topics
공식 코드Document Similarity for Texts of Varying Lengths via Hidden Topics
https://github.com/JindongGu/Awesome-Prompting-on-Vision-Language-Model
공식 코드A Systematic Survey of Prompt Engineering on Vision-Language Foundation Models
https://github.com/Junction4Nako/mvp_pytorch
공식 코드MVPTR: Multi-Level Semantic Alignment for Vision-Language Pre-Training via Multi-Stage Learning
https://github.com/KAIST-VICLab/TDSM
공식 코드TDSM: Triplet Diffusion for Skeleton-Text Matching in Zero-Shot Action Recognition
https://github.com/KunpengLi1994/VSRN
공식 코드https://github.com/LabyrinthineLeo/DISCO
공식 코드https://github.com/MILVLG/mmnas
공식 코드https://github.com/NTMC-Community/MatchZoo
공식 코드https://github.com/NTMC-Community/MatchZoo-Studio
공식 코드MatchZoo: A Learning, Practicing, and Developing System for Neural Text Matching
https://github.com/Paranioar/DBL
공식 코드Deep Boosting Learning: A Brand-new Cooperative Approach for Image-Text Matching
https://github.com/Paranioar/SGRAF
공식 코드https://github.com/RUC-WSM/WD-Match
공식 코드Wasserstein Distance Regularized Sequence Representation for Text Matching in Asymmetrical Domains
https://github.com/Roc-Ng/HANet
공식 코드HANet: Hierarchical Alignment Networks for Video-Text Retrieval
https://github.com/SeleenaJM/CapEval
공식 코드https://github.com/Shuyu-XJTU/APTM
공식 코드https://github.com/Sxing2/CLIP-Test-time-Counterattacks
공식 코드https://github.com/VoyageWang/IteRPrimE
공식 코드https://github.com/Wangt-CN/MTFN-RR-PyTorch-Code
공식 코드Matching Images and Text with Multi-modal Tensor Fusion and Re-ranking
https://github.com/YuanEZhou/Grounded-Image-Captioning
공식 코드More Grounded Image Captioning by Distilling Image-Text Matching Model
https://github.com/YulongBonjour/BrainCLIP
공식 코드https://github.com/ailab-kyunghee/cm2_dvc
공식 코드Do You Remember? Dense Video Captioning with Cross-Modal Memory Retrieval
https://github.com/allenai/medicat
공식 코드MedICaT: A Dataset of Medical Images, Captions, and Textual References
https://github.com/amazon-science/MAGID
공식 코드MAGID: An Automated Pipeline for Generating Synthetic Multi-modal Datasets
https://github.com/ameenali/videomatch
공식 코드https://github.com/anosorae/irra
공식 코드Cross-Modal Implicit Relation Reasoning and Aligning for Text-to-Image Person Retrieval
https://github.com/anusfoil/llaqo
공식 코드LLaQo: Towards a Query-Based Coach in Expressive Music Performance Assessment
https://github.com/apple/ml-no-token-left-behind
공식 코드No Token Left Behind: Explainability-Aided Image Classification and Generation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.