Detecting customized moments and highlights from videos given natural language (NL) user
queries is an important but under-studied topic. One of the challenges in pursuing this …

Abstract Video Moment Retrieval (MR) and Highlight Detection (HD) have attracted
significant attention due to the growing demand for video analysis. Recent approaches treat …

In video highlight detection, the goal is to identify the interesting moments within an unedited
video. Although the audio component of the video provides important cues for highlight …

Temporal Grounding is to identify specific moments or highlights from a video corresponding
to textual descriptions. Typical approaches in temporal grounding treat all video clips …

Video highlight detection can greatly simplify video browsing, potentially paving the way for
a wide range of applications. Existing efforts are mostly fully-supervised, requiring humans …

In this paper, we investigate video summarization in the supervised setting. Since video
summarization is subjective to the preference of the end-user, the design of a unique model …

The goal of video highlight detection is to select the most attractive segments from a long
video to depict the most interesting parts of the video. Existing methods typically focus on …

Humans easily miss events in their surroundings due to limited short-term memory and field
of view. This happens, for example, while watching an instructor's machine repair …

In this paper, we explore the use of large language models (LLMs) to enhance video
moment retrieval (VMR) by integrating general knowledge and pseudo-events as priors. We …

Given a face image, most of previous works in gaze estimation infer the gaze via a well-
trained model with supervised training. However, the distribution of test data may be very …