Gan inversion: A survey
GAN inversion aims to invert a given image back into the latent space of a pretrained GAN
model so that the image can be faithfully reconstructed from the inverted code by the …
model so that the image can be faithfully reconstructed from the inverted code by the …
Diffusionrig: Learning personalized priors for facial appearance editing
We address the problem of learning person-specific facial priors from a small number (eg,
20) of portrait photos of the same person. This enables us to edit this specific person's facial …
20) of portrait photos of the same person. This enables us to edit this specific person's facial …
Learning to relight portrait images via a virtual light stage and synthetic-to-real adaptation
Given a portrait image of a person and an environment map of the target lighting, portrait
relighting aims to re-illuminate the person in the image as if the person appeared in an …
relighting aims to re-illuminate the person in the image as if the person appeared in an …
[PDF][PDF] Total relighting: learning to relight portraits for background replacement.
Compositing a person into a scene to look like they are really there is a fundamental
technique in visual effects, with many other applications such as smartphone photography …
technique in visual effects, with many other applications such as smartphone photography …
Canet: A context-aware network for shadow removal
Z Chen, C Long, L Zhang… - Proceedings of the IEEE …, 2021 - openaccess.thecvf.com
In this paper, we propose a novel two-stage context-aware network named CANet for
shadow removal, in which the contextual information from non-shadow regions is transferred …
shadow removal, in which the contextual information from non-shadow regions is transferred …
[HTML][HTML] Real-time radiance fields for single-image portrait view synthesis
We present a one-shot method to infer and render a photorealistic 3D representation from a
single unposed image (eg, face portrait) in real-time. Given a single RGB input, our image …
single unposed image (eg, face portrait) in real-time. Given a single RGB input, our image …
Deep symmetric network for underexposed image enhancement with recurrent attentional learning
Underexposed image enhancement is of importance in many research domains. In this
paper, we take this problem as image feature transformation between the underexposed …
paper, we take this problem as image feature transformation between the underexposed …
Neural light transport for relighting and view synthesis
The light transport (LT) of a scene describes how it appears under different lighting
conditions from different viewing directions, and complete knowledge of a scene's LT …
conditions from different viewing directions, and complete knowledge of a scene's LT …
Learning from synthetic shadows for shadow detection and removal
N Inoue, T Yamasaki - … on Circuits and Systems for Video …, 2020 - ieeexplore.ieee.org
Shadow removal is an essential task in computer vision and computer graphics. Recent
shadow removal approaches all train convolutional neural networks (CNN) on real paired …
shadow removal approaches all train convolutional neural networks (CNN) on real paired …
Perceptual artifacts localization for image synthesis tasks
Recent advancements in deep generative models have facilitated the creation of photo-
realistic images across various tasks. However, these generated images often exhibit …
realistic images across various tasks. However, these generated images often exhibit …