Face hallucination using generative adversarial networks | |
| Author | Raju, Nagalapelli Prithvi |
| Subject(s) | Machine learning Neural networks (Computer science) Surveillance detection Image processing-Digital techniques |
| Note | A research study submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Computer Science and Information Management |
| Publisher | Asian Institute of Technology |
| Abstract | The evolution of surveillance techniques in the modern era has powered AI to develop algorithms that provide numerous opportunities to improve security and well being. Surveillance cameras monitoring a wide field of view can result in capturing indiscernible faces which makes human activity monitoring and recognition impossible. Single Image Super-resolution (SISR) provides a feasible solution to enhance such faces in order to recognise the individuals. However, lack of ground truth high-resolution methods make it infeasible to develop such devised methods to develop a standard SISR model. In this research, I explore the challenge of building a SISR system from a limited set of unaligned pairs of Low-res and High-res images. Though none of the models could produce substantial results, each one of those unravel problems in an unsupervised setting. I propose a model that leverages literature from Style Transfer to achieve the reconstruction of noisy low-res face images, but in an extremely specific domain. I further conclude the research for exploration of models and domains in Deep Learning where we might find the possible solution to the problem. |
| Year | 2020 |
| Type | Research Study Project Report (RSPR) |
| School | School of Engineering and Technology (SET) |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Computer Science (CS) |
| Chairperson(s) | Dailey, Mathew N.; |
| Examination Committee(s) | Mongkol Ekpanyapong;Attaphongse Taparugssanagorn; |
| Scholarship Donor(s) | AIT Fellowship; |
| Degree | Research Studies Project Report (M. Eng.) - Asian Institute of Technology, 2020 |