Scan2Part: Fine-grained and Hierarchical Part-level Understanding of Real-World 3D Scans

no code implementations • 6 Jun 2022 • Alexandr Notchenko, Vladislav Ishimtsev, Alexey Artemov, Vadim Selyutin, Emil Bogomolov, Evgeny Burnaev

We propose Scan2Part, a method to segment individual parts of objects in real-world, noisy indoor RGB-D scans.

Scene Understanding

Towards Part-Based Understanding of RGB-D Scans

1 code implementation • CVPR 2021 • Alexey Bokhovkin, Vladislav Ishimtsev, Emil Bogomolov, Denis Zorin, Alexey Artemov, Evgeny Burnaev, Angela Dai

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-grained understanding is required to enable interactions with objects and their functional understanding.

3D Instance Segmentation Object +2

DEF: Deep Estimation of Sharp Geometric Features in 3D Shapes

1 code implementation • 30 Nov 2020 • Albert Matveev, Ruslan Rakhimov, Alexey Artemov, Gleb Bobrovskikh, Vage Egiazarian, Emil Bogomolov, Daniele Panozzo, Denis Zorin, Evgeny Burnaev

We propose Deep Estimators of Features (DEFs), a learning-based framework for predicting sharp geometric features in sampled 3D shapes.

Making DensePose fast and light

1 code implementation • 26 Jun 2020 • Ruslan Rakhimov, Emil Bogomolov, Alexandr Notchenko, Fung Mao, Alexey Artemov, Denis Zorin, Evgeny Burnaev

DensePose estimation task is a significant step forward for enhancing user experience computer vision applications ranging from augmented reality to cloth fitting.

3D Human Pose Estimation Quantization