Computer Vision / Neural Networks and Deep Learning

Pairwise Relational Network – New Method for Face Recognition

28 November 2018

Pairwise Relational Network face recognition

Pairwise Relational Network – New Method for Face Recognition

With the rapid progress of deep learning in the past few years, many computer vision problems have been tackled and solved with human or even beyond human performance. One of…

Learning Physical Skills from Youtube Videos using Deep Reinforcement Learning

6 November 2018

Learning Physical Skills from Youtube Videos using Deep Reinforcement Learning

Realistic, humanlike chracters represent a very important area of computer animation. These characters are vital components of many applications, such as cartoons, computer games, cinematic special effects, virtual reality,…

“The Sound of Pixels”: Self-supervised Method for Sound Localisation and Separation

29 October 2018

“The Sound of Pixels”: Self-supervised Method for Sound Localisation and Separation

We, as human beings are able to digest a sound video with almost no effort. Being able to detect and track objects within the frames of a video allows us…

3D Hair Reconstruction Out of In-the-Wild Videos

22 October 2018

3D Hair Reconstruction Out of In-the-Wild Videos

3D hair reconstruction is a problem with numerous applications in different areas such as Virtual Reality, Augmented Reality, video games, medical software, etc. As a non-trivial problem, researchers have proposed…

Head Reconstruction from Internet Photos

15 October 2018

Head Reconstruction from Internet Photos

Methods that reconstruct 3D models of people’s heads from images need to account for varying 3D pose, lighting, non-rigid changes due to expressions, relatively smooth surfaces of faces, ears, and…

True Face Super-Resolution Upscaling with the Facial Component Heatmaps

1 October 2018

True Face Super-Resolution Upscaling with the Facial Component Heatmaps

The performance of the most facial analysis techniques relies on the resolution of the corresponding image. Face alignment or face identification is not going to work correctly when the resolution…

Deforming Autoencoders (DAEs) – Learning Disentangled Representations

21 September 2018

Deforming Autoencoders (DAEs) – Learning Disentangled Representations

Generative Models are drawing a lot of attention within the Machine Learning research community. This kind of models has practical applications in different domains. Two of the most commonly used…

Facial Surface and Texture Synthesis via GAN

3 September 2018

Facial Surface and Texture Synthesis via GAN

Deep networks can be extremely powerful and effective in answering complex questions. But it is also well-known that in order to train a really complex model, you’ll need lots and…