The recent wave of AI-generated content (AIGC) has witnessed substantial success in
computer vision, with the diffusion model playing a crucial role in this achievement. Due to …

Food is essential for human life and it is fundamental to the human experience. Food-related
study may support multifarious applications and services, such as guiding human behavior …

Human activity recognition (HAR) systems attempt to automatically identify and analyze
human activities using acquired information from various types of sensors. Although several …

Abstract We propose Anticipative Video Transformer (AVT), an end-to-end attention-based
video modeling architecture that attends to the previously observed video in order to …

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 …

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 …

Algorithms for the action segmentation task typically use temporal models to predict what
action is occurring at each frame for a minute-long daily activity. Recent studies have shown …

Temporally locating and classifying action segments in long untrimmed videos is of
particular interest to many applications like surveillance and robotics. While traditional …

This paper introduces a unified framework for video action segmentation via sequence to
sequence (seq2seq) translation in a fully and timestamp supervised setup. In contrast to …

A key requirement for leveraging supervised deep learning methods is the availability of
large, labeled datasets. Unfortunately, in the context of RGB-D scene understanding, very …