activity
20182023
most citedText-To-4D Dynamic Scene Generation

23 citations · 33 across the 6 of their papers we have counts for

collaborators

11 papers

cs.CV2023

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…

cs.CV2023★ 1 cited

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…

cs.CV2023★ 23 cited

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…

cs.CV2021

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…

cs.CV2021★ 8 cited

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…

cs.CV2021

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…