Recent developments in video analysis of sports and computer vision techniques have
achieved significant improvements to enable a variety of critical operations. To provide …

Temporal action segmentation (TAS) in videos aims at densely identifying video frames in
minutes-long videos with multiple action classes. As a long-range video understanding task …

Large pretrained (eg," foundation") models exhibit distinct capabilities depending on the
domain of data they are trained on. While these domains are generic, they may only barely …

This work proposes TimeChat a time-sensitive multimodal large language model specifically
designed for long video understanding. Our model incorporates two key architectural …

Temporal action segmentation is crucial for understanding long-form videos. Previous works
on this task commonly adopt an iterative refinement paradigm by using multi-stage models …

Recently, video moment retrieval and highlight detection (MR/HD) are being spotlighted as
the demand for video understanding is drastically increased. The key objective of MR/HD is …

Action recognition models have shown a promising capability to classify human actions in
short video clips. In a real scenario, multiple correlated human actions commonly occur in …

Video data are witnessing exponential growth, and extracting summarized information is
challenging. It is always necessary to reduce the load of video traffic for the efficient video …

This paper presents a new method for supervised video summarization. To overcome
drawbacks of existing RNN-based summarization architectures, that relate to the modeling …

Video summarization has recently engaged increasing attention in computer vision
communities. However, the scarcity of annotated data has been a key obstacle in this task …