103 citations · 502 across the 43 of their papers we have counts for
13 papers · 1 filter
Enhancing Perceptual Attributes with Bayesian Style Generation
Aliaksandr Siarohin, Gloria Zen, Nicu Sebe +1
Deep learning has brought an unprecedented progress in computer vision and significant advances have been made in predicting subjective properties inherent to visual data (e.g., me…
Predicting Group Cohesiveness in Images
Shreya Ghosh, Abhinav Dhall, Nicu Sebe +1
The cohesiveness of a group is an essential indicator of the emotional state, structure and success of a group of people. We study the factors that influence the perception of grou…
Animating Arbitrary Objects via Deep Motion Transfer
Aliaksandr Siarohin, Stéphane Lathuilière, Sergey Tulyakov +2
This paper introduces a novel deep learning framework for image animation. Given an input image with a target object and a driving video sequence depicting a moving object, our fra…
Deep Micro-Dictionary Learning and Coding Network
Hao Tang, Heng Wei, Wei Xiao +4
In this paper, we propose a novel Deep Micro-Dictionary Learning and Coding Network (DDLCN). DDLCN has most of the standard deep learning layers (pooling, fully, connected, input/o…
GestureGAN for Hand Gesture-to-Gesture Translation in the Wild
Hao Tang, Wei Wang, Dan Xu +2
Hand gesture-to-gesture translation in the wild is a challenging task since hand gestures can have arbitrary poses, sizes, locations and self-occlusions. Therefore, this task requi…
Unsupervised Adversarial Depth Estimation using Cycled Generative Networks
Andrea Pilzer, Dan Xu, Mihai Marian Puscas +2
While recent deep monocular depth estimation approaches based on supervised regression have achieved remarkable performance, costly ground truth annotations are required during tra…