Image-text matching is a fundamental task to bridge vision and language. The critical
challenge lies in accurately learning the semantic similarity between these two …

Image-text matching, as a fundamental cross-modal task, bridges vision and language. The
key challenge lies in accurately learning the semantic similarity of these two heterogeneous …

Webly supervised learning has attracted increasing attention for its effectiveness in
exploring publicly accessible data at scale without manual annotation. However, most …

Image-text matching is a challenging task due to vast discrepancies between the visual and
textual modalities. Existing solutions tend to focus on a limited set of strongly aligned or …

Abstract Image-Text Retrieval (ITR) is essentially a ranking problem. Given a query caption,
the goal is to rank candidate images by relevance, from large to small. The current ITR …

Using stickers in online chatting is very prevalent on social media platforms, where the
stickers used in the conversation can express someone's intention/emotion/attitude in a …

Image-text retrieval is a fundamental task in bridging the semantics between vision and
language. The key challenge lies in accurately and efficiently learning the semantic …

Image-text matching is a fundamental task in bridging the semantics between vision and
language. The key challenge lies in establishing accurate alignment between two …

CLIP4Clip model transferred from the CLIP has been the de-factor standard to solve the
video clip retrieval task from frame-level input, triggering the surge of CLIP4Clip-based …

Graph structures can represent rich semantic relationships, but currently, image-text
matching methods have not been well applied. How to efficiently achieve graph learning …