| Author | Honari, Sina |
| Title | Feature extraction on faces : from landmark localization to depth estimation |
| URL | http://hdl.handle.net/1866/22658  |
| Publication Date | 2019 |
| Date Accessioned | 2019-11-27 20:09:50 |
| University/Publisher | Université de Montréal |
| Subjects/Keywords | Neural networks; Deep learning; Convolutional networks; Supervised learning; Unsupervised learning; Semi-supervised learning; Coarse-to-fine architectures; Landmark localization; Depth estimation; Face rotation; Face replacement; Réseaux neuronaux; Apprentissage profond; Réseaux neuronaux de convolution; Apprentissage supervisé; Apprentissage non-supervisé; Apprentissage semi-supervisé; Architectures grossières à fines; Localisation de points clés; Estimation de la profondeur; Rotation de visage; Échange de visage; Applied Sciences - Artificial Intelligence / Sciences appliqués et technologie - Intelligence artificielle (UMI : 0800) |
| Contributors | Vincent, Pascal (advisor); Pal, Christopher (advisor) |
| Rights | Unrestricted |
| Country of Publication | ca |
| Record ID | handle:1866/22658 |
| Repository | montreal |
| Date Indexed | 2020-08-12 |
| Issued Date | 2019-06-19 00:00:00 |
Sample Search Hits | Sample Images
…83 5.4. Recent Developments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 vii Chapter 6. Recombinator Networks: Learning Coarse-to-Fine Feature Aggregation . . 85 6.1…
…2.4. Face Rotation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 Chapter 3. Prologue to First Article…
…79 Chapter 5. Prologue to Second Article. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 5.1. Article Details…
…101 Chapter 7. Prologue to Third Article . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106 7.1. Article Details…
…135 Chapter 9. Prologue to Fourth Article . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139 9.1. Article Details…
…10.3.4. Adversarial Image-to-Image Transformation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153 10.3.4.1. 10.4. CycleGAN…
…155 10.4.2. DepthNet Evaluation on Unpaired Faces and Comparison to other Models . . . . . 158 10.4.3. Face Rotation, Replacement and Adversarial Repair . . . . . . . . . . . . . . . . . . . . . . . . . 163 10.4.3.1. Face Rotation…
…162 10.5 Face projection of an identity to different poses of other identities . . . . . . . . . . . . . . . . . . . 164 10.6 Face projection of an identity to different poses of other identities . . . . . . . . . . . . . . . . . . . 164 10.7 Re…
