We showcased our new app BeQu at Glow 2019. For two days users could try out exclusive content and win products from our partner brands!
In our app, we link the right users with the products that interest them in the form of mobile games, user surveys and state-of-the-art augmented reality. BeQu turns simple shopping into an emotional, shareable experience that takes the pulse of the hard-to-reach millennials up to the Alpha generation.
Explored Make-Up Style Transfer with BeautyGAN.
The network is trained with make-up and non-make-up pictures. It’s possible to apply different make-up styles (eg. from Influencers from Instagram) to your image. See the picture for examples.
An ASMR game prototype this time together with @pavethem. The goal of the game is to draw latte art and satisfy your customers. We used fluid dynamics (base from stable fluids) on the GPU to simulate the foam.
More …Different kind of training for CR7 to use him as a virtual avatar with Pix2Pix (using the code of datitran).
I generated the dataset from this video. The Network is trained with OpenCV landmark images from a source video. The same landmark detection is applied to the webcam output.
Experimenting with moving images and visual importance. The example shows the Oscar’s feed on Instagram. This ML network is trained with eye-tracking heatmaps of UIs. Red shows areas of high interest and blue of low interest. This is quite useful for designing flows within apps.
I applied this to the designs from our app Quizfriends. Looks cool, but it seems like it only learned to highlight high contrast areas. It would be even more useful to know where the user is watching first.
