Neural style transfer: A review
The seminal work of Gatys et al. demonstrated the power of Convolutional Neural Networks
(CNNs) in creating artistic imagery by separating and recombining image content and style …
(CNNs) in creating artistic imagery by separating and recombining image content and style …
Deep learning for image colorization: Current and future prospects
Image colorization, as an essential problem in computer vision (CV), has attracted an
increasing amount of researchers attention in recent years, especially deep learning-based …
increasing amount of researchers attention in recent years, especially deep learning-based …
NeRF-Art: Text-Driven Neural Radiance Fields Stylization
As a powerful representation of 3D scenes, the neural radiance field (NeRF) enables high-
quality novel view synthesis from multi-view images. Stylizing NeRF, however, remains …
quality novel view synthesis from multi-view images. Stylizing NeRF, however, remains …
Ccpl: Contrastive coherence preserving loss for versatile style transfer
In this paper, we aim to devise a universally versatile style transfer method capable of
performing artistic, photo-realistic, and video style transfer jointly, without seeing videos …
performing artistic, photo-realistic, and video style transfer jointly, without seeing videos …
Deep exemplar-based colorization
We propose the first deep learning approach for exemplar-based local colorization. Given a
reference color image, our convolutional neural network directly maps a grayscale image to …
reference color image, our convolutional neural network directly maps a grayscale image to …
Avatar-net: Multi-scale zero-shot style transfer by feature decoration
Zero-shot artistic style transfer is an important image synthesis problem aiming at
transferring arbitrary style into content images. However, the trade-off between the …
transferring arbitrary style into content images. However, the trade-off between the …
Geometry-consistent generative adversarial networks for one-sided unsupervised domain map**
Unsupervised domain map** aims to learn a function GXY to translate domain X to Y in
the absence of paired examples. Finding the optimal GXY without paired data is an ill-posed …
the absence of paired examples. Finding the optimal GXY without paired data is an ill-posed …
Parallax attention for unsupervised stereo correspondence learning
Stereo image pairs encode 3D scene cues into stereo correspondences between the left
and right images. To exploit 3D cues within stereo images, recent CNN based methods …
and right images. To exploit 3D cues within stereo images, recent CNN based methods …
Cross view capture for stereo image super-resolution
Stereo image super-resolution exploits additional features from cross view image pairs for
high resolution (HR) image reconstruction. Recently, several new methods have been …
high resolution (HR) image reconstruction. Recently, several new methods have been …