https://github.com/Chaolei98/FreeZAD
CoCa: Contrastive Captioners are Image-Text Foundation Models
Papers with Code 아카이브
Image Retrieval with Multi-Modal Query
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 4
- 평가표
- 3
- 보존된 평가 기록
- 15
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/ChihchengHsieh/AttnGAN_Implementation
AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks
https://github.com/Chloejay/image_caption_app
https://github.com/CryhanFang/CLIP2Video
Fine-grained Video-Text Retrieval with Hierarchical Graph Reasoning
https://github.com/Data-drone/cvnd_image_captioning
https://github.com/Djmcflush/Quantum-Hackathon
https://github.com/FreddeFrallan/Multilingual-CLIP
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/Gahyeonkim09/AAPL
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/Gowthamkar6/Image-captioning-using-CNN-RNN
https://github.com/GuessWhatGame/clevr
https://github.com/HyeonwooNoh/DPPnet
Image Question Answering using Convolutional Neural Network with Dynamic Parameter Prediction
https://github.com/IMvision12/keras-vision-models
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/IllgamhoDuck/ResTR
https://github.com/ImperialNLP/BertGen
VL-BERT: Pre-training of Generic Visual-Linguistic Representations
https://github.com/IzabelaKrupinska/PROJBAD
Deep Visual-Semantic Alignments for Generating Image Descriptions
https://github.com/JoshuaPlacidi/MS-COCO-Object-Tags
VinVL: Revisiting Visual Representations in Vision-Language Models
https://github.com/JoshuaPlacidi/MS-COCO-Tags
VinVL: Revisiting Visual Representations in Vision-Language Models
https://github.com/JunweiLiang/DualAttentionNetwork
Dual Attention Networks for Multimodal Reasoning and Matching
https://github.com/Kaushalya/medclip
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/KohavTal/SCAE_Project
https://github.com/KubotaYugo/Impression-CLIP-Contrastive-Shape-Impression-Embedding-for-Fonts
Impression-CLIP: Contrastive Shape-Impression Embedding for Fonts
https://github.com/Lieberk/Paddle-AoA-Captioning
Deep Visual-Semantic Alignments for Generating Image Descriptions
https://github.com/Maymaher/StackGANv2
AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks
https://github.com/MicPie/clasp
Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision
https://github.com/MindCode-4/code-3/tree/main/florence2
https://github.com/MindSpore-scientific-2/code-10/tree/main/PolyLoss
Universal Weighting Metric Learning for Cross-Modal Matching
https://github.com/MindSpore-scientific-2/code-8/tree/main/SMOTE
https://github.com/Mrnoorsingh/image-caption
https://github.com/MuhammadMomin93/Stacked-Capsule-Autoencoders-PyTorch
https://github.com/MysteryVaibhav/SCAN
https://github.com/NYU-DICE-Lab/open_clip
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/Neznakomec/ml-project-transformers
https://github.com/NicholasKX/ShowAndTell
https://github.com/NicoleBonnie/AMAN
https://github.com/OML-Team/open-metric-learning
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/PKU-ICST-MIPL/MCSM_TIP2018
Modality-specific Cross-modal Similarity Measurement with Recurrent Attention Network
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.