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

Procedural activity understanding requires perceiving human actions in terms of a broader
task, where multiple keysteps are performed in sequence across a long video to reach a …

Abstract Object State Changes (OSCs) are pivotal for video understanding. While humans
can effortlessly generalize OSC understanding from familiar to unknown objects current …

We address the task of generating temporally consistent and physically plausible images of
actions and object state transformations. Given an input image and a text prompt describing …

We address the task of generating temporally consistent and physically plausible images of
actions and object state transformations. Given an input image and a text prompt describing …

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 …

Action Quality Assessment (AQA) is a challenging task involving analyzing fine-grained
technical subactions, aligning high-level visual-semantic representations, and exploring …

We address the problem of extracting key steps from unlabeled procedural videos,
motivated by the potential of Augmented Reality (AR) headsets to revolutionize job training …

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 explore the capability of an agent to construct a logical sequence of action
steps thereby assembling a strategic procedural plan. This plan is crucial for navigating from …