Image Retrieval with Multi-Modal Query
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The problem of retrieving images from a database based on a multi-modal (image- text) query. Specifically, the query text prompts some modification in the query image and the task is to retrieve images with the desired modifications.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/noagarcia/context-art-classification
https://github.com/nopperl/clip_arxiv_pmc
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https://github.com/oarriaga/neural_image_captioning
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InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks
https://github.com/oxygenlu/ratlip
AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks
https://github.com/pathmmu-benchmark/pathmmu
https://github.com/pengfeiliheu/mumc
Self-supervised vision-language pretraining for Medical visual question answering
https://github.com/penghu-cs/RCL
https://github.com/phanideepgampa/stacked-capsule-networks
https://github.com/pharmolix/openbiomed
https://github.com/phenixace/molregpt
https://github.com/pioneerAlpha/BanglaText2ImageGeneration
AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks
https://github.com/prabhupad26/100daysofML
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/priscillalui/StackGAN-Stories
AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks
https://github.com/pshroff04/Dual_Path_CNN
Dual-Path Convolutional Image-Text Embeddings with Instance Loss
https://github.com/pskrunner14/descriptor
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/altclip
AltCLIP: Altering the Language Encoder in CLIP for Extended Language Capabilities
https://github.com/pwc-1/Paper-8/tree/main/blip
https://github.com/pwc-1/Paper-8/tree/main/clip
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/qinyang79/decl
https://github.com/qxzha/UGNCL
https://github.com/ramanakshay/clip
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/rebnej/lick-caption-bias
https://github.com/redcaps-dataset/redcaps-downloader
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/rightlit/cycle-image-gan-rev
AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks
https://github.com/rinnakk/japanese-clip
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/rishavbb/Image_Captioning
https://github.com/rishikmani/sort-of-clevr
https://github.com/rmokady/clip_prefix_caption
Oscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks
https://github.com/rohitbhaskar/online-ads-repository
VSE++: Improving Visual-Semantic Embeddings with Hard Negatives
https://github.com/rosinality/relation-networks-pytorch
https://github.com/roxanasoto/AttGanESRGAN
AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks
https://github.com/s-a-malik/multi-few
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/sajjjadayobi/CLIPfa
Learning Transferable Visual Models From Natural Language Supervision
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.