Traffic accident detection and anticipation is an obstinate road safety problem and
painstaking efforts have been devoted. With the rapid growth of video data, Vision-based …

Multimedia recommendation methods aim to discover the user preference on the multi-
modal information to enhance the collaborative filtering (CF) based recommender system …

Spatio-temporal video grounding aims to localize the aligned visual tube corresponding to a
language query. Existing techniques achieve such alignment by exploiting dense boundary …

Given an untrimmed video and a sentence query, video moment retrieval using language
(VMR) aims to locate a target query-relevant moment. Since the untrimmed video is …

Prompt tuning, a recently emerging paradigm, enables the powerful vision-language pre-
training models to adapt to downstream tasks in a parameter-and data-efficient way, by …

Almost all previous text-to-video retrieval works assume that videos are pre-trimmed with
short durations. However, in practice, videos are generally untrimmed containing much …

Abstract In recent times, Vision-Language Models (VLMs) have been trained under two
predominant paradigms. Generative training has enabled Multimodal Large Language …

Multi-modal recommendation systems, which integrate diverse types of information, have
gained widespread attention in recent years. However, compared to traditional collaborative …

Video Moment Retrieval (VMR) targets to retrieve the specific moment corresponding to a
sentence query from an untrimmed video. Although recent respectable works have made …

This paper identifies two kinds of redundancy in the current VideoQA paradigm. Specifically,
the current video encoders tend to holistically embed all video clues at different granularities …