Human activity recognition is a key to a lot of applications such as healthcare and smart
home. In this study, we provide a comprehensive survey on recent advances and challenges …

Deep learning (DL) is being successfully applied across multiple domains, yet these models
learn in a most artificial way: they require large quantities of labeled data to grasp even …

Building a robot that can understand and learn to interact by watching humans has inspired
several vision problems. However, despite some successful results on static datasets, it …

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 …

Recent successes in image synthesis are powered by large-scale diffusion models.
However, most methods are currently limited to either text-or image-conditioned generation …

Our world offers a never-ending stream of visual stimuli, yet today's vision systems only
accurately recognize patterns within a few seconds. These systems understand the present …

We propose to forecast future hand-object interactions given an egocentric video. Instead of
predicting action labels or pixels, we directly predict the hand motion trajectory and the …

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 …

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 …

Streaming video recognition reasons about objects and their actions in every frame of a
video. A good streaming recognition model captures both long-term dynamics and short …