54 citations · 123 across the 19 of their papers we have counts for
4 papers · 1 filter
Towards Practical Control of Singular Values of Convolutional Layers
Alexandra Senderovich, Ekaterina Bulatova, Anton Obukhov +1
In general, convolutional neural networks (CNNs) are easy to train, but their essential properties, such as generalization error and adversarial robustness, are hard to control. Re…
DiffDreamer: Towards Consistent Unsupervised Single-view Scene Extrapolation with Conditional Diffusion Models
Shengqu Cai, Eric Ryan Chan, Songyou Peng +4
Scene extrapolation -- the idea of generating novel views by flying into a given image -- is a promising, yet challenging task. For each predicted frame, a joint inpainting and 3D…
TT-NF: Tensor Train Neural Fields
Anton Obukhov, Mikhail Usvyatsov, Christos Sakaridis +2
Learning neural fields has been an active topic in deep learning research, focusing, among other issues, on finding more compact and easy-to-fit representations. In this paper, we…
Pix2NeRF: Unsupervised Conditional -GAN for Single Image to Neural Radiance Fields Translation
Shengqu Cai, Anton Obukhov, Dengxin Dai +1
We propose a pipeline to generate Neural Radiance Fields~(NeRF) of an object or a scene of a specific class, conditioned on a single input image. This is a challenging task, as tra…