Hilton Bristow
Hilton Bristow
CSIRO, Queensland University of Technology
Verified email at csiro.au
TitleCited byYear
Fast convolutional sparse coding
H Bristow, A Eriksson, S Lucey
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2013
2552013
Dense semantic correspondence where every pixel is a classifier
H Bristow, J Valmadre, S Lucey
Proceedings of the IEEE International Conference on Computer Vision, 4024-4031, 2015
402015
Why do linear SVMs trained on HOG features perform so well?
H Bristow, S Lucey
arXiv preprint arXiv:1406.2419, 2014
352014
Optimization methods for convolutional sparse coding
H Bristow, S Lucey
arXiv preprint arXiv:1406.2407, 2014
322014
In defense of gradient-based alignment on densely sampled sparse features
H Bristow, S Lucey
Dense Image Correspondences for Computer Vision, 135-152, 2016
122016
V1-inspired features induce a weighted margin in SVMs
H Bristow, S Lucey
European Conference on Computer Vision, 59-72, 2012
42012
Regression-based image alignment for general object categories
H Bristow, S Lucey
arXiv preprint arXiv:1407.1957, 2014
32014
Registration and representation in computer vision
HK Bristow
Queensland University of Technology, 2016
2016
Home/Publications
Y Han, Y Yang, Y Yan, Z Ma, N Sebe, X Zhou, C Zhang
IEEE Transactions on Image Processing (IEEE T-IP) 22 (12), 5071-5084, 2013
2013
Analysing X-means Clustering for Reproducibility, Validity and Effectiveness
H Bristow
The system can't perform the operation now. Try again later.
Articles 1–10