Fast convolutional sparse coding H Bristow, A Eriksson, S Lucey Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2013 | 418 | 2013 |
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 | 70 | 2015 |
Optimization methods for convolutional sparse coding H Bristow, S Lucey arXiv preprint arXiv:1406.2407, 2014 | 54 | 2014 |
Why do linear SVMs trained on HOG features perform so well? H Bristow, S Lucey arXiv preprint arXiv:1406.2419, 2014 | 52 | 2014 |
In defense of gradient-based alignment on densely sampled sparse features H Bristow, S Lucey Dense image correspondences for computer vision, 135-152, 2016 | 16 | 2016 |
V1-inspired features induce a weighted margin in SVMs H Bristow, S Lucey Computer Vision–ECCV 2012: 12th European Conference on Computer Vision …, 2012 | 6 | 2012 |
Regression-based image alignment for general object categories H Bristow, S Lucey arXiv preprint arXiv:1407.1957, 2014 | 3 | 2014 |
Registration and representation in computer vision HK Bristow Queensland University of Technology, 2016 | | 2016 |
Analysing X-means Clustering for Reproducibility, Validity and Effectiveness H Bristow | | |