Abstract We present EgoExo-Fitness, a new full-body action understanding dataset,
featuring fitness sequence videos recorded from synchronized egocentric and fixed …

Action Quality Assessment (AQA) quantitatively evaluates the quality of human actions,
providing automated assessments that reduce biases in human judgment. Its applications …

In this report, we present our solutions to the EgoVis Challenges in CVPR 2024, including
five tracks in the Ego4D challenge and three tracks in the EPIC-Kitchens challenge. Building …

Compared with visual signals, Inertial Measurement Units (IMUs) placed on human limbs
can capture accurate motion signals while being robust to lighting variation and occlusion …

We introduce LaGTran, a novel framework that utilizes text supervision to guide robust
transfer of discriminative knowledge from labeled source to unlabeled target data with …

We present EMBED (Egocentric Models Built with Exocentric Data), a method designed to
transform exocentric video-language data for egocentric video representation learning …

We introduce Vinci, a real-time embodied smart assistant built upon an egocentric vision-
language model. Designed for deployment on portable devices such as smartphones and …

Most existing video understanding benchmarks for multimodal large language models
(MLLMs) focus only on short videos. The limited number of benchmarks for long video …

Traditional dense video captioning predominantly focuses on edited exocentric footage.
These videos are filmed from an external perspective and generally feature distinct …

Recent advancements in Multi-modal Large Language Models (MLLMs) have opened new
avenues for applications in Embodied AI. Building on previous work, EgoThink, we introduce …