Search Results for author: Anna Vorontsova

Found 9 papers, 4 papers with code

Floorplan-Aware Camera Poses Refinement

no code implementations10 Oct 2022 Anna Sokolova, Filipp Nikitin, Anna Vorontsova, Anton Konushin

Processing large indoor scenes is a challenging task, as scan registration and camera trajectory estimation methods accumulate errors across time.

3D Reconstruction Model Optimization

Single-Stage 3D Geometry-Preserving Depth Estimation Model Training on Dataset Mixtures With Uncalibrated Stereo Data

no code implementations CVPR 2022 Nikolay Patakin, Anna Vorontsova, Mikhail Artemyev, Anton Konushin

On the contrary, we propose GP2, General-Purpose and Geometry-Preserving training scheme, and show that conventional SVDE models can learn correct shifts themselves without any post-processing, benefiting from using stereo data even in the geometry-preserving setting.

3D Reconstruction Depth Estimation

FCAF3D: Fully Convolutional Anchor-Free 3D Object Detection

2 code implementations1 Dec 2021 Danila Rukhovich, Anna Vorontsova, Anton Konushin

Existing 3D object detection methods make prior assumptions on the geometry of objects, and we argue that it limits their generalization ability.

3D Object Detection object-detection

ImVoxelNet: Image to Voxels Projection for Monocular and Multi-View General-Purpose 3D Object Detection

3 code implementations2 Jun 2021 Danila Rukhovich, Anna Vorontsova, Anton Konushin

To address this problem, we propose ImVoxelNet, a novel fully convolutional method of 3D object detection based on monocular or multi-view RGB images.

Monocular 3D Object Detection object-detection +1

Towards General Purpose Geometry-Preserving Single-View Depth Estimation

1 code implementation25 Sep 2020 Mikhail Romanov, Nikolay Patatkin, Anna Vorontsova, Sergey Nikolenko, Anton Konushin, Dmitry Senyushkin

Our work shows that a model trained on this data along with conventional datasets can gain accuracy while predicting correct scene geometry.

Monocular Depth Estimation Scene Understanding

Training Deep SLAM on Single Frames

1 code implementation11 Dec 2019 Igor Slinko, Anna Vorontsova, Dmitry Zhukov, Olga Barinova, Anton Konushin

We train visual odometry model on synthetic data and do not use ground truth poses hence this model can be considered unsupervised.

Optical Flow Estimation Visual Odometry

Scene Motion Decomposition for Learnable Visual Odometry

no code implementations16 Jul 2019 Igor Slinko, Anna Vorontsova, Filipp Konokhov, Olga Barinova, Anton Konushin

Optical Flow (OF) and depth are commonly used for visual odometry since they provide sufficient information about camera ego-motion in a rigid scene.

Motion Estimation Optical Flow Estimation +1

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