233 citations · 1.1k across the 115 of their papers we have counts for
27 papers · 1 filter
Relightable 3D Head Portraits from a Smartphone Video
Artem Sevastopolsky, Savva Ignatiev, Gonzalo Ferrer +2
In this work, a system for creating a relightable 3D portrait of a human head is presented. Our neural pipeline operates on a sequence of frames captured by a smartphone camera wit…
Towards Part-Based Understanding of RGB-D Scans
Alexey Bokhovkin, Vladislav Ishimtsev, Emil Bogomolov +4
Recent advances in 3D semantic scene understanding have shown impressive progress in 3D instance segmentation, enabling object-level reasoning about 3D scenes; however, a finer-gra…
Loss Barcode: A Topological Measure of Escapability in Loss Landscapes
Serguei Barannikov, Daria Voronkova, Alexander Mironenko +4
Neural network training is commonly based on SGD. However, the understanding of SGD's ability to converge to good local minima, given the non-convex nature of loss functions and th…
AI-enabled Prediction of eSports Player Performance Using the Data from Heterogeneous Sensors
Anton Smerdov, Evgeny Burnaev, Andrey Somov +1
The emerging progress of eSports lacks the tools for ensuring high-quality analytics and training in Pro and amateur eSports teams. We report on an Artificial Intelligence (AI) ena…
How Good MVSNets Are at Depth Fusion
Oleg Voynov, Aleksandr Safin, Savva Ignatyev +1
We study the effects of the additional input to deep multi-view stereo methods in the form of low-quality sensor depth. We modify two state-of-the-art deep multi-view stereo method…
DEF: Deep Estimation of Sharp Geometric Features in 3D Shapes
Albert Matveev, Ruslan Rakhimov, Alexey Artemov +6
We propose Deep Estimators of Features (DEFs), a learning-based framework for predicting sharp geometric features in sampled 3D shapes. Differently from existing data-driven method…