activity
20162019
most citedDetecting the Moment of Completion: Temporal Models for Localising Action Completion

5 citations · 5 across the 2 of their papers we have counts for

collaborators

16 papers

cs.CV2020

Supervision Levels Scale (SLS)

Dima Damen, Michael Wray

We propose a three-dimensional discrete and incremental scale to encode a method's level of supervision - i.e. the data and labels used when training a model to achieve a given per…

cs.CV20207 cited

The EPIC-KITCHENS Dataset: Collection, Challenges and Baselines

Dima Damen, Hazel Doughty, Giovanni Maria Farinella +8

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 objects, t…

cs.CV2020

Multi-Modal Domain Adaptation for Fine-Grained Action Recognition

Jonathan Munro, Dima Damen

Fine-grained action recognition datasets exhibit environmental bias, where multiple video sequences are captured from a limited number of environments. Training a model in one envi…

cs.CV2019

Action Modifiers: Learning from Adverbs in Instructional Videos

Hazel Doughty, Ivan Laptev, Walterio Mayol-Cuevas +1

We present a method to learn a representation for adverbs from instructional videos using weak supervision from the accompanying narrations. Key to our method is the fact that the…

cs.CV2019

Weakly-Supervised Completion Moment Detection using Temporal Attention

Farnoosh Heidarivincheh, Majid Mirmehdi, Dima Damen

Monitoring the progression of an action towards completion offers fine grained insight into the actor's behaviour. In this work, we target detecting the completion moment of action…

cs.CV20195 cited

Sit-to-Stand Analysis in the Wild using Silhouettes for Longitudinal Health Monitoring

Alessandro Masullo, Tilo Burghardt, Toby Perrett +2

We present the first fully automated Sit-to-Stand or Stand-to-Sit (StS) analysis framework for long-term monitoring of patients in free-living environments using video silhouettes.…