117 citations · 150 across the 9 of their papers we have counts for
12 papers
Replay: Multi-modal Multi-view Acted Videos for Casual Holography
Roman Shapovalov, Yanir Kleiman, Ignacio Rocco +6
We introduce Replay, a collection of multi-view, multi-modal videos of humans interacting socially. Each scene is filmed in high production quality, from different viewpoints with…
Real-time volumetric rendering of dynamic humans
Ignacio Rocco, Iurii Makarov, Filippos Kokkinos +4
We present a method for fast 3D reconstruction and real-time rendering of dynamic humans from monocular videos with accompanying parametric body fits. Our method can reconstruct a…
Text-To-4D Dynamic Scene Generation
Uriel Singer, Shelly Sheynin, Adam Polyak +8
We present MAV3D (Make-A-Video3D), a method for generating three-dimensional dynamic scenes from text descriptions. Our approach uses a 4D dynamic Neural Radiance Field (NeRF), whi…
Poly-NL: Linear Complexity Non-local Layers with Polynomials
Francesca Babiloni, Ioannis Marras, Filippos Kokkinos +3
Spatial self-attention layers, in the form of Non-Local blocks, introduce long-range dependencies in Convolutional Neural Networks by computing pairwise similarities among all poss…
To The Point: Correspondence-driven monocular 3D category reconstruction
Filippos Kokkinos, Iasonas Kokkinos
We present To The Point (TTP), a method for reconstructing 3D objects from a single image using 2D to 3D correspondences learned from weak supervision. We recover a 3D shape from a…
Learning monocular 3D reconstruction of articulated categories from motion
Filippos Kokkinos, Iasonas Kokkinos
Monocular 3D reconstruction of articulated object categories is challenging due to the lack of training data and the inherent ill-posedness of the problem. In this work we use vide…
Pixel Adaptive Filtering Units
Filippos Kokkinos, Ioannis Marras, Matteo Maggioni +2
State-of-the-art methods for computer vision rely heavily on the translation equivariance and spatial sharing properties of convolutional layers without explicitly taking into cons…
Microscopy Image Restoration with Deep Wiener-Kolmogorov filters
Valeriya Pronina, Filippos Kokkinos, Dmitry V. Dylov +1
Microscopy is a powerful visualization tool in biology, enabling the study of cells, tissues, and the fundamental biological processes; yet, the observed images typically suffer fr…
Iterative Residual CNNs for Burst Photography Applications
Filippos Kokkinos, Stamatios Lefkimmiatis
Modern inexpensive imaging sensors suffer from inherent hardware constraints which often result in captured images of poor quality. Among the most common ways to deal with such lim…
Iterative Joint Image Demosaicking and Denoising using a Residual Denoising Network
Filippos Kokkinos, Stamatios Lefkimmiatis
Modern digital cameras rely on the sequential execution of separate image processing steps to produce realistic images. The first two steps are usually related to denoising and dem…
Deep Image Demosaicking using a Cascade of Convolutional Residual Denoising Networks
Filippos Kokkinos, Stamatios Lefkimmiatis
Demosaicking and denoising are among the most crucial steps of modern digital camera pipelines and their joint treatment is a highly ill-posed inverse problem where at-least two-th…
Structural Attention Neural Networks for improved sentiment analysis
Filippos Kokkinos, Alexandros Potamianos
We introduce a tree-structured attention neural network for sentences and small phrases and apply it to the problem of sentiment classification. Our model expands the current recur…