We present a novel unsupervised domain adaption method for person
re-ide...
Novel digital data sources and tools like machine learning (ML) and
arti...
Learning visual representation of high quality is essential for image
cl...
We address the problem of network quantization, that is, reducing bit-wi...
A shift-invariant variational autoencoder (shift-VAE) is developed as an...
Network quantization aims at reducing bit-widths of weights and/or
activ...
This paper introduces a large-scale Korean speech dataset, called VOTE40...
In this paper, we introduce FairFaceGAN, a fairness-aware facial
Image-t...
Convolutional neural networks (CNNs) have allowed remarkable advances in...
Fair representation learning aims to encode invariant representation wit...
Deep learning, based on which many modern algorithms operate, is well kn...
We address the problem of semantic correspondence, that is, establishing...
We address the problem of semantic correspondence, that is, establishing...
In this paper, we propose Squeezed Convolutional Variational AutoEncoder...