We introduce Ego4D, a massive-scale egocentric video dataset and benchmark suite. It
offers 3,670 hours of daily-life activity video spanning hundreds of scenarios (household …

This paper introduces the pipeline to extend the largest dataset in egocentric vision, EPIC-
KITCHENS. The effort culminates in EPIC-KITCHENS-100, a collection of 100 hours, 20M …

We focus on multi-modal fusion for egocentric action recognition, and propose a novel
architecture for multi-modal temporal-binding, ie the combination of modalities within a …

Since its introduction in 2018, EPIC-KITCHENS has attracted attention as the largest
egocentric video benchmark, offering a unique viewpoint on people's interaction with …

First-person vision is gaining interest as it offers a unique viewpoint on people's interaction
with objects, their attention, and even intention. However, progress in this challenging …

Current video retrieval efforts all found their evaluation on an instance-based assumption,
that only a single caption is relevant to a query video and vice versa. We demonstrate that …

Despite the recent progress in video understanding and the continuous rate of improvement
in temporal action localization throughout the years, it is still unclear how far (or close?) we …

The egocentric action recognition EAR field has recently increased its popularity due to the
affordable and lightweight wearable cameras available nowadays such as GoPro and …

Temporal action detection (TAD) is extensively studied in the video understanding
community by generally following the object detection pipeline in images. However, complex …

In temporal action segmentation, Timestamp Supervision requires only a handful of labelled
frames per video sequence. For unlabelled frames, previous works rely on assigning hard …