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Showing 201–225 of 246 papers

TitleStatusHype
Image Semantic Relation Generation—0
Cross-modal Contrastive Attention Model for Medical Report Generation—0
Every picture tells a story: Image-grounded controllable stylistic story generation—0
Discovering Bugs in Vision Models using Off-the-shelf Image Generation and Captioning—0
Paired Cross-Modal Data Augmentation for Fine-Grained Image-to-Text Retrieval—0
SRCB at SemEval-2022 Task 5: Pretraining Based Image to Text Late Sequential Fusion System for Multimodal Misogynous Meme Identification—0
Delving into the Openness of CLIPCode0
Multilingual Image Corpus – Towards a Multimodal and Multilingual Dataset—0
Uncertainty-based Cross-Modal Retrieval with Probabilistic Representations—0
COTS: Collaborative Two-Stream Vision-Language Pre-Training Model for Cross-Modal Retrieval—0
Characterizing and Understanding the Behavior of Quantized Models for Reliable DeploymentCode0
Two-stream Hierarchical Similarity Reasoning for Image-text Matching—0
A Thousand Words Are Worth More Than a Picture: Natural Language-Centric Outside-Knowledge Visual Question Answering—0
Transform-Retrieve-Generate: Natural Language-Centric Outside-Knowledge Visual Question Answering—0
EI-CLIP: Entity-Aware Interventional Contrastive Learning for E-Commerce Cross-Modal Retrieval—0
Self-Supervised Image-to-Text and Text-to-Image SynthesisCode0
Exploration into Translation-Equivariant Image QuantizationCode0
Utilizing Resource-Rich Language Datasets for End-to-End Scene Text Recognition in Resource-Poor Languages—0
Contrastive Learning of Visual-Semantic Embeddings—0
Survey of Visual-Semantic Embedding Methods for Zero-Shot Image Retrieval—0
Knowledge driven Description Synthesis for Floor Plan Interpretation—0
Hierarchical Gumbel Attention Network for Text-based Person Search—0
Cross-Modal Alignment with Mixture Experts Neural Network for Intral-City Retail Recommendation—0
Development of a New Image-to-text Conversion System for Pashto, Farsi and Traditional Chinese—0
Multimodal Intelligence: Representation Learning, Information Fusion, and Applications—0
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