25 citations · 45 across the 8 of their papers we have counts for
6 papers · 1 filter
Grow-Push-Prune: aligning deep discriminants for effective structural network compression
Qing Tian, Tal Arbel, James J. Clark
Most of today's popular deep architectures are hand-engineered to be generalists. However, this design procedure usually leads to massive redundant, useless, or even harmful featur…
Instance Segmentation based Semantic Matting for Compositing Applications
Guanqing Hu, James J. Clark
Image compositing is a key step in film making and image editing that aims to segment a foreground object and combine it with a new background. Automatic image compositing can be d…
Task dependent Deep LDA pruning of neural networks
Qing Tian, Tal Arbel, James J. Clark
With deep learning's success, a limited number of popular deep nets have been widely adopted for various vision tasks. However, this usually results in unnecessarily high complexit…
Personalization of Saliency Estimation
Bingqing Yu, James J. Clark
Most existing saliency models use low-level features or task descriptions when generating attention predictions. However, the link between observer characteristics and gaze pattern…
WAYLA - Generating Images from Eye Movements
Bingqing Yu, James J. Clark
We present a method for reconstructing images viewed by observers based only on their eye movements. By exploring the relationships between gaze patterns and image stimuli, the "Wh…
Attentional Push: Augmenting Salience with Shared Attention Modeling
Siavash Gorji, James J. Clark
We present a novel visual attention tracking technique based on Shared Attention modeling. Our proposed method models the viewer as a participant in the activity occurring in the s…