https://github.com/lcfractal/tgdt
Efficient Token-Guided Image-Text Retrieval with Consistent Multimodal Contrastive Training
Papers with Code 아카이브
Text Retrieval
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Text Retrieval is the task of finding the most text result (such as an answer, paragraph, or passage) given a query (which could be a question, keywords, or any relevant text)
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/leondgarse/keras_cv_attention_models/tree/main/keras_cv_attention_models/beit
https://github.com/lichengunc/pretrain-vl-data
https://github.com/liyongqi67/minder
https://github.com/lucidrains/x-clip
https://github.com/luigisigillo/gwit
https://github.com/lyon-nlp/mteb-french
https://github.com/m-bain/webvid
Frozen in Time: A Joint Video and Image Encoder for End-to-End Retrieval
https://github.com/m2man/hada
HADA: A Graph-based Amalgamation Framework in Image-text Retrieval
https://github.com/mayug/freeze-align
From Unimodal to Multimodal: Scaling up Projectors to Align Modalities
https://github.com/mbzuai-oryx/unimed-clip
PMC-CLIP: Contrastive Language-Image Pre-training using Biomedical Documents
https://github.com/microsoft/VSE_Gradient
Dissecting Deep Metric Learning Losses for Image-Text Retrieval
https://github.com/microsoft/seed-encoder
Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval
https://github.com/modelscope/modelscope
mPLUG: Effective and Efficient Vision-Language Learning by Cross-modal Skip-connections
https://github.com/naver-ai/hype
https://github.com/necla-ml/SNLI-VE
https://github.com/nerdimite/neuro-symbolic-ai-soc
https://github.com/nidhikamal-emb/DPR_repo
Knowledge Guided Text Retrieval and Reading for Open Domain Question Answering
https://github.com/ninatu/howtocaption
https://github.com/nthakur20/income
Efficiently Teaching an Effective Dense Retriever with Balanced Topic Aware Sampling
https://github.com/nttcslab/eval-audio-repr
M2D2: Exploring General-purpose Audio-Language Representations Beyond CLAP
https://github.com/nttcslab/m2d
M2D2: Exploring General-purpose Audio-Language Representations Beyond CLAP
https://github.com/oaqa/knn4qa
https://github.com/opengvlab/internvl-mmdetseg
InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks
https://github.com/osu-nlp-group/hipporag
BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models
https://github.com/paullerner/viquae
WIT: Wikipedia-based Image Text Dataset for Multimodal Multilingual Machine Learning
https://github.com/peizeli96/MHys
Multimodal Hypothetical Summary for Retrieval-based Multi-image Question Answering
https://github.com/pku-yuangroup/video-bench
https://github.com/princetonvisualai/mqvr
Frozen in Time: A Joint Video and Image Encoder for End-to-End Retrieval
https://github.com/pwc-1/Paper-5/tree/main/mistral
https://github.com/pwc-1/Paper-8/tree/main/align
Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision
https://github.com/pwc-1/Paper-8/tree/main/blip
https://github.com/roudimit/AVLnet
CLIP4Clip: An Empirical Study of CLIP for End to End Video Clip Retrieval
https://github.com/rwightman/pytorch-image-models
https://github.com/s-nlp/russe_detox_2022
https://github.com/salesforce/ALBEF
Align before Fuse: Vision and Language Representation Learning with Momentum Distillation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.