Search Results for author: Jose Caballero

Found 15 papers, 7 papers with code

Smile, Be Happy :) Emoji Embedding for Visual Sentiment Analysis

no code implementations14 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.

Sentiment Analysis Transfer Learning

Deep Hashing using Entropy Regularised Product Quantisation Network

no code implementations11 Feb 2019 Jo Schlemper, Jose Caballero, Andy Aitken, Joost van Amersfoort

In large scale systems, approximate nearest neighbour search is a crucial algorithm to enable efficient data retrievals.

Convolutional Recurrent Neural Networks for Dynamic MR Image Reconstruction

4 code implementations5 Dec 2017 Chen Qin, Jo Schlemper, Jose Caballero, Anthony Price, Joseph V. Hajnal, Daniel Rueckert

In particular, the proposed architecture embeds the structure of the traditional iterative algorithms, efficiently modelling the recurrence of the iterative reconstruction stages by using recurrent hidden connections over such iterations.

Image Reconstruction Temporal Sequences

Frame Interpolation with Multi-Scale Deep Loss Functions and Generative Adversarial Networks

no code implementations16 Nov 2017 Joost van Amersfoort, Wenzhe Shi, Alejandro Acosta, Francisco Massa, Johannes Totz, Zehan Wang, Jose Caballero

To improve the quality of synthesised intermediate video frames, our network is jointly supervised at different levels with a perceptual loss function that consists of an adversarial and two content losses.

Checkerboard artifact free sub-pixel convolution: A note on sub-pixel convolution, resize convolution and convolution resize

3 code implementations10 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.

A Deep Cascade of Convolutional Neural Networks for Dynamic MR Image Reconstruction

4 code implementations8 Apr 2017 Jo Schlemper, Jose Caballero, Joseph V. Hajnal, Anthony Price, Daniel Rueckert

Firstly, we show that when each 2D image frame is reconstructed independently, the proposed method outperforms state-of-the-art 2D compressed sensing approaches such as dictionary learning-based MR image reconstruction, in terms of reconstruction error and reconstruction speed.

Dictionary Learning Image Reconstruction

Amortised MAP Inference for Image Super-resolution

no code implementations14 Oct 2016 Casper Kaae Sønderby, Jose Caballero, Lucas Theis, Wenzhe Shi, Ferenc Huszár

We show that, using this architecture, the amortised MAP inference problem reduces to minimising the cross-entropy between two distributions, similar to training generative models.

Denoising Image Super-Resolution +1

Is the deconvolution layer the same as a convolutional layer?

6 code implementations22 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.

Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network

133 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.

Image Super-Resolution

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