no code implementations • 14 Jul 2019 • Ziad Al-Halah, Andrew Aitken, Wenzhe Shi, Jose Caballero
Additionally, we introduce a novel emoji representation based on their visual emotional response which supports a deeper understanding of the emoji modality and their usage on social media.
3 code implementations • 10 Jul 2017 • Andrew Aitken, Christian Ledig, Lucas Theis, Jose Caballero, Zehan Wang, Wenzhe Shi
Compared to sub-pixel convolution initialized with schemes designed for standard convolution kernels, it is free from checkerboard artifacts immediately after initialization.
no code implementations • CVPR 2017 • Jose Caballero, Christian Ledig, Andrew Aitken, Alejandro Acosta, Johannes Totz, Zehan Wang, Wenzhe Shi
Convolutional neural networks have enabled accurate image super-resolution in real-time.
Ranked #11 on Video Super-Resolution on MSU Video Upscalers: Quality Enhancement (VMAF metric)
6 code implementations • 22 Sep 2016 • Wenzhe Shi, Jose Caballero, Lucas Theis, Ferenc Huszar, Andrew Aitken, Christian Ledig, Zehan Wang
In this note, we want to focus on aspects related to two questions most people asked us at CVPR about the network we presented.
138 code implementations • CVPR 2017 • Christian Ledig, Lucas Theis, Ferenc Huszar, Jose Caballero, Andrew Cunningham, Alejandro Acosta, Andrew Aitken, Alykhan Tejani, Johannes Totz, Zehan Wang, Wenzhe Shi
The adversarial loss pushes our solution to the natural image manifold using a discriminator network that is trained to differentiate between the super-resolved images and original photo-realistic images.
Ranked #3 on Image Super-Resolution on VggFace2 - 8x upscaling