In this paper, we aim to establish an automatic, scalable pipeline for denoising the large-
scale instructional dataset and construct a high-quality video-text dataset with multiple …

Recent advances in Video Large Language Models (Video-LLMs) have demonstrated their
great potential in general-purpose video understanding. To verify the significance of these …

Narrative visualization effectively transforms data into engaging stories, making complex
information accessible to a broad audience. Large models, essential for narrative …

Abstract Generating Audio Description (AD) for movies is a challenging task that requires
fine-grained visual understanding and an awareness of the characters and their names …

Learning to localize temporal boundaries of procedure steps in instructional videos is
challenging due to the limited availability of annotated large-scale training videos. Recent …

In this paper we propose VidLA an approach for video-language alignment at scale. There
are two major limitations of previous video-language alignment approaches. First they do …

In this paper, we consider the problem of temporally aligning the video and texts from
instructional videos, specifically, given a long-term video, and associated text sentences, our …

Video description generates natural language sentences that describe the subject, verb, and
objects of the targeted Video. The video description has been used to help visually impaired …

Short video platforms, such as YouTube, Instagram, or TikTok, are used by billions of users
globally. These platforms expose users to harmful content, ranging from clickbait or physical …

Text-video retrieval (TVR) identifies relevant videos based on textual queries. Existing
methods are limited by their ability to understand and connect different modalities, resulting …