2 citations · 2 across the 1 of their papers we have counts for
4 papers
Scan2Part: Fine-grained and Hierarchical Part-level Understanding of Real-World 3D Scans
Alexandr Notchenko, Vladislav Ishimtsev, Alexey Artemov +3
We propose Scan2Part, a method to segment individual parts of objects in real-world, noisy indoor RGB-D scans. To this end, we vary the part hierarchies of objects in indoor scenes…
Making DensePose fast and light
Ruslan Rakhimov, Emil Bogomolov, Alexandr Notchenko +4
DensePose estimation task is a significant step forward for enhancing user experience computer vision applications ranging from augmented reality to cloth fitting. Existing neural…
Perceptual deep depth super-resolution
Oleg Voynov, Alexey Artemov, Vage Egiazarian +4
RGBD images, combining high-resolution color and lower-resolution depth from various types of depth sensors, are increasingly common. One can significantly improve the resolution o…
Large-Scale Shape Retrieval with Sparse 3D Convolutional Neural Networks
Alexandr Notchenko, Ermek Kapushev, Evgeny Burnaev
In this paper we present results of performance evaluation of S3DCNN - a Sparse 3D Convolutional Neural Network - on a large-scale 3D Shape benchmark ModelNet40, and measure how it…