activity
20182021
most citedSit-to-Stand Analysis in the Wild using Silhouettes for Longitudinal Health Monitoring

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

collaborators

7 papers

cs.CV2021

Temporal-Relational CrossTransformers for Few-Shot Action Recognition

Toby Perrett, Alessandro Masullo, Tilo Burghardt +2

We propose a novel approach to few-shot action recognition, finding temporally-corresponding frame tuples between the query and videos in the support set. Distinct from previous fe…

math.AG2020

Crystalline cohomology over general bases

A. M. Masullo

Building on ideas of Berthelot, we develop a crystalline cohomology formalism over divided power rings for any ring , allowing -flat . For a smooth…

cs.CV2020

Meta-Learning with Context-Agnostic Initialisations

Toby Perrett, Alessandro Masullo, Tilo Burghardt +2

Meta-learning approaches have addressed few-shot problems by finding initialisations suited for fine-tuning to target tasks. Often there are additional properties within training d…

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.…

cs.CV2018

CaloriNet: From silhouettes to calorie estimation in private environments

Alessandro Masullo, Tilo Burghardt, Dima Damen +3

We propose a novel deep fusion architecture, CaloriNet, for the online estimation of energy expenditure for free living monitoring in private environments, where RGB data is discar…

cs.CV2018

Semantically Selective Augmentation for Deep Compact Person Re-Identification

Víctor Ponce-López, Tilo Burghardt, Sion Hannunna +3

We present a deep person re-identification approach that combines semantically selective, deep data augmentation with clustering-based network compression to generate high performa…