Papers Semantic Image-Text Similarity
“Semantic Image-Text Similarity” 태그가 달린 논문 4편 · 필터 해제
Visual-Text Cross Alignment: Refining the Similarity Score in Vision-Language Models
It has recently been discovered that using a pre-trained vision-language model (VLM), e.g., CLIP, to align a whole query image with several finer text descriptions generated by a large language model can significantly en…
Few-Shot LearningLanguage ModelingLanguage ModellingLarge Language Model+3Linguistic-Aware Patch Slimming Framework for Fine-grained Cross-Modal Alignment
Cross-modal alignment aims to build a bridge connecting vision and language. It is an important multi-modal task that efficiently learns the semantic similarities between images and texts. Traditional fine-grained al…
cross-modal alignmentCross-Modal RetrievalImage RetrievalImage-to-Text Retrieval+4MURAL: Multimodal, Multitask Retrieval Across Languages
Both image-caption pairs and translation pairs provide the means to learn deep representations of and connections between languages. We use both types of pairs in MURAL (MUltimodal, MUltitask Representations Across Langu…
Cross-Modal RetrievalImage-text matchingRetrievalSemantic Image Similarity+4Learning the Best Pooling Strategy for Visual Semantic Embedding
Visual Semantic Embedding (VSE) is a dominant approach for vision-language retrieval, which aims at learning a deep embedding space such that visual data are embedded close to their semantic text labels or descriptions. …
Cross-Modal Information RetrievalImage-text RetrievalRetrievalSemantic Image-Text Similarity+2