64 citations · 224 across the 21 of their papers we have counts for
4 papers · 1 filter
Predicting the Future: A Jointly Learnt Model for Action Anticipation
Harshala Gammulle, Simon Denman, Sridha Sridharan +1
Inspired by human neurological structures for action anticipation, we present an action anticipation model that enables the prediction of plausible future actions by forecasting bo…
Coupled Generative Adversarial Network for Continuous Fine-grained Action Segmentation
Harshala Gammulle, Tharindu Fernando, Simon Denman +2
We propose a novel conditional GAN (cGAN) model for continuous fine-grained human action segmentation, that utilises multi-modal data and learned scene context information. The pro…
Forecasting Future Action Sequences with Neural Memory Networks
Harshala Gammulle, Simon Denman, Sridha Sridharan +1
We propose a novel neural memory network based framework for future action sequence forecasting. This is a challenging task where we have to consider short-term, within sequence re…
Fine-grained Action Segmentation using the Semi-Supervised Action GAN
Harshala Gammulle, Simon Denman, Sridha Sridharan +1
In this paper we address the problem of continuous fine-grained action segmentation, in which multiple actions are present in an unsegmented video stream. The challenge for this ta…