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Image-text matching

Image-Text Matching is a subtask within Cross-Modal Retrieval (CMR) that involves establishing associations between images and corresponding textual descriptions. The goal is to retrieve an image given a textual query or, conversely, retrieve a textual description given an image query. This task is challenging due to the heterogeneity gap between image and text data representations. Image-text matching is used in applications such as content-based image search, visual question answering, and multimodal summarization.

Assessing Brittleness of Image-Text Retrieval Benchmarks from Vision-Language Models Perspective

Papers

Showing 91100 of 188 papers

TitleStatusHype
Integrating Language Guidance Into Image-Text Matching for Correcting False NegativesCode0
Plug-and-Play Regulators for Image-Text MatchingCode1
Increasing Textual Context Size Boosts Medical Image-Text MatchingCode0
BiCro: Noisy Correspondence Rectification for Multi-modality Data via Bi-directional Cross-modal Similarity ConsistencyCode1
Cross-Modal Implicit Relation Reasoning and Aligning for Text-to-Image Person RetrievalCode2
Refined Vision-Language Modeling for Fine-grained Multi-modal Pre-training0
Selectively Hard Negative Mining for Alleviating Gradient Vanishing in Image-Text Matching0
BrainCLIP: Bridging Brain and Visual-Linguistic Representation Via CLIP for Generic Natural Visual Stimulus DecodingCode1
VL-Match: Enhancing Vision-Language Pretraining with Token-Level and Instance-Level Matching0
Weakly Supervised Referring Image Segmentation with Intra-Chunk and Inter-Chunk Consistency0
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