Search Results for author: Evangelos Ntavelis

Found 7 papers, 6 papers with code

AutoDecoding Latent 3D Diffusion Models

1 code implementation NeurIPS 2023 Evangelos Ntavelis, Aliaksandr Siarohin, Kyle Olszewski, Chaoyang Wang, Luc van Gool, Sergey Tulyakov

We present a novel approach to the generation of static and articulated 3D assets that has a 3D autodecoder at its core.

StyleGenes: Discrete and Efficient Latent Distributions for GANs

no code implementations30 Apr 2023 Evangelos Ntavelis, Mohamad Shahbazi, Iason Kastanis, Radu Timofte, Martin Danelljan, Luc van Gool

Thus, by independently sampling a variant for each gene and combining them into the final latent vector, our approach can represent a vast number of unique latent samples from a compact set of learnable parameters.

Disentanglement

NeRF-GAN Distillation for Efficient 3D-Aware Generation with Convolutions

1 code implementation22 Mar 2023 Mohamad Shahbazi, Evangelos Ntavelis, Alessio Tonioni, Edo Collins, Danda Pani Paudel, Martin Danelljan, Luc van Gool

Pose-conditioned convolutional generative models struggle with high-quality 3D-consistent image generation from single-view datasets, due to their lack of sufficient 3D priors.

Image Generation Inductive Bias

Arbitrary-Scale Image Synthesis

1 code implementation CVPR 2022 Evangelos Ntavelis, Mohamad Shahbazi, Iason Kastanis, Radu Timofte, Martin Danelljan, Luc van Gool

Positional encodings have enabled recent works to train a single adversarial network that can generate images of different scales.

Image Generation

SkyCam: A Dataset of Sky Images and their Irradiance values

1 code implementation6 May 2021 Evangelos Ntavelis, Jan Remund, Philipp Schmid

Recent advances in Computer Vision and Deep Learning have enabled astonishing results in a variety of fields and applications.

AIM 2020 Challenge on Image Extreme Inpainting

3 code implementations2 Oct 2020 Evangelos Ntavelis, Andrés Romero, Siavash Bigdeli, Radu Timofte

This report focuses on proposed solutions and results for two different tracks on extreme image inpainting: classical image inpainting and semantically guided image inpainting.

Image Inpainting Semantic Segmentation

SESAME: Semantic Editing of Scenes by Adding, Manipulating or Erasing Objects

1 code implementation ECCV 2020 Evangelos Ntavelis, Andrés Romero, Iason Kastanis, Luc van Gool, Radu Timofte

In contrast to previous methods that employ a discriminator that trivially concatenates semantics and image as an input, the SESAME discriminator is composed of two input streams that independently process the image and its semantics, using the latter to manipulate the results of the former.

Image Manipulation Image-to-Image Translation

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