Cancer research encompasses data across various scales, modalities, and resolutions, from
screening and diagnostic imaging to digitized histopathology slides to various types of …

With the success of large language models (LLMs) integrating the vision model into LLMs to
build vision-language foundation models has gained much more interest recently. However …

What will the future be? We wonder! In this survey, we explore the gap between current
research in egocentric vision and the ever-anticipated future, where wearable computing …

We present RAFTformer, a real-time action forecasting transformer for latency aware real-
world action forecasting applications. RAFTformer is a two-stage fully transformer based …

Human action anticipation aims at predicting what people will do in the future based on past
observations. In this paper we introduce Uncertainty-aware Action Decoupling Transformer …

We study the problem of future step anticipation in procedural videos. Given a video of an
ongoing procedural activity, we predict a plausible next procedure step described in rich …

Anticipation problem has been studied considering different aspects such as predicting
humans' locations, predicting hands and objects trajectories, and forecasting actions and …

Human-object interaction (HOI) and temporal dynamics along the motion paths are the most
important visual cues for egocentric action anticipation. Especially, interaction regions …

Although existing methods for action anticipation have shown considerably improved
performance on the predictability of future events in videos, the way they exploit information …

Abstract Objects are crucial for understanding human-object interactions. By identifying the
relevant objects, one can also predict potential future interactions or actions that may occur …