1 code implementation • 26 Feb 2024 • Saeed Khorram, Mingqi Jiang, Mohamad Shahbazi, Mohamad H. Danesh, Li Fuxin
In the presence of imbalanced multi-class training data, GANs tend to favor classes with more samples, leading to the generation of low-quality and less diverse samples in tail classes.
no code implementations • 10 Jan 2024 • Mohamad Shahbazi, Liesbeth Claessens, Michael Niemeyer, Edo Collins, Alessio Tonioni, Luc van Gool, Federico Tombari
We introduce InseRF, a novel method for generative object insertion in the NeRF reconstructions of 3D scenes.
no code implementations • 30 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.
1 code implementation • 22 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.
no code implementations • ICCV 2023 • Shengqu Cai, Eric Ryan Chan, Songyou Peng, Mohamad Shahbazi, Anton Obukhov, Luc van Gool, Gordon Wetzstein
Scene extrapolation -- the idea of generating novel views by flying into a given image -- is a promising, yet challenging task.
Ranked #1 on Perpetual View Generation on LHQ
1 code implementation • 11 May 2022 • Chuqiao Li, Zhiwu Huang, Danda Pani Paudel, Yabin Wang, Mohamad Shahbazi, Xiaopeng Hong, Luc van Gool
Within the proposed benchmark, we explore some commonly known essentials of standard continual learning.
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.
1 code implementation • ICLR 2022 • Mohamad Shahbazi, Martin Danelljan, Danda Pani Paudel, Luc van Gool
On the contrary, we observe that class-conditioning causes mode collapse in limited data settings, where unconditional learning leads to satisfactory generative ability.
1 code implementation • CVPR 2021 • Mohamad Shahbazi, Zhiwu Huang, Danda Pani Paudel, Ajad Chhatkuli, Luc van Gool
To address this problem, we introduce a new GAN transfer method to explicitly propagate the knowledge from the old classes to the new classes.