488 citations · 740 across the 12 of their papers we have counts for
12 papers
Masked Discriminators for Content-Consistent Unpaired Image-to-Image Translation
Bonifaz Stuhr, Jürgen Brauer, Bernhard Schick +1
A common goal of unpaired image-to-image translation is to preserve content consistency between source images and translated images while mimicking the style of the target domain.…
Hierarchical Residual Attention Network for Single Image Super-Resolution
Parichehr Behjati, Pau Rodriguez, Armin Mehri +3
Convolutional neural networks are the most successful models in single image super-resolution. Deeper networks, residual connections, and attention mechanisms have further improved…
OverNet: Lightweight Multi-Scale Super-Resolution with Overscaling Network
Parichehr Behjati, Pau Rodriguez, Armin Mehri +3
Super-resolution (SR) has achieved great success due to the development of deep convolutional neural networks (CNNs). However, as the depth and width of the networks increase, CNN-…
Pay attention to the activations: a modular attention mechanism for fine-grained image recognition
Pau Rodríguez López, Diego Velazquez Dorta, Guillem Cucurull Preixens +3
Fine-grained image recognition is central to many multimedia tasks such as search, retrieval and captioning. Unfortunately, these tasks are still challenging since the appearance o…
From 2D to 3D Geodesic-based Garment Matching
Meysam Madadi, Egils Avots, Sergio Escalera +3
A new approach for 2D to 3D garment retexturing is proposed based on Gaussian mixture models and thin plate splines (TPS). An automatically segmented garment of an individual is ma…
Attend and Rectify: a Gated Attention Mechanism for Fine-Grained Recovery
Pau Rodríguez, Josep M. Gonfaus, Guillem Cucurull +2
We propose a novel attention mechanism to enhance Convolutional Neural Networks for fine-grained recognition. It learns to attend to lower-level feature activations without requiri…
Beyond One-hot Encoding: lower dimensional target embedding
Pau Rodríguez, Miguel A. Bautista, Jordi Gonzàlez +1
Target encoding plays a central role when learning Convolutional Neural Networks. In this realm, One-hot encoding is the most prevalent strategy due to its simplicity. However, thi…
Deep Inference of Personality Traits by Integrating Image and Word Use in Social Networks
Guillem Cucurull, Pau Rodríguez, V. Oguz Yazici +3
Social media, as a major platform for communication and information exchange, is a rich repository of the opinions and sentiments of 2.3 billion users about a vast spectrum of topi…
End-to-end Global to Local CNN Learning for Hand Pose Recovery in Depth Data
Meysam Madadi, Sergio Escalera, Xavier Baro +1
Despite recent advances in 3D pose estimation of human hands, especially thanks to the advent of CNNs and depth cameras, this task is still far from being solved. This is mainly du…
End-to-end semantic face segmentation with conditional random fields as convolutional, recurrent and adversarial networks
Umut Güçlü, Yağmur Güçlütürk, Meysam Madadi +5
Recent years have seen a sharp increase in the number of related yet distinct advances in semantic segmentation. Here, we tackle this problem by leveraging the respective strengths…
Regularizing CNNs with Locally Constrained Decorrelations
Pau Rodríguez, Jordi Gonzàlez, Guillem Cucurull +2
Regularization is key for deep learning since it allows training more complex models while keeping lower levels of overfitting. However, the most prevalent regularizations do not l…
Enhanced Mixtures of Part Model for Human Pose Estimation
Wenjuan Gong, Yongzhen Huang, Jordi Gonzalez +1
Mixture of parts model has been successfully applied to 2D human pose estimation problem either as explicitly trained body part model or as latent variables for the whole human bod…