Search Results for author: Anna Vorontsova

Found 14 papers, 7 papers with code

FCAF3D: Fully Convolutional Anchor-Free 3D Object Detection

3 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 +1

OneFormer3D: One Transformer for Unified Point Cloud Segmentation

1 code implementation24 Nov 2023 Maxim Kolodiazhnyi, Anna Vorontsova, Anton Konushin, Danila Rukhovich

Semantic, instance, and panoptic segmentation of 3D point clouds have been addressed using task-specific models of distinct design.

3D Instance Segmentation 3D Object Detection +4

TR3D: Towards Real-Time Indoor 3D Object Detection

1 code implementation6 Feb 2023 Danila Rukhovich, Anna Vorontsova, Anton Konushin

Our model with early feature fusion, which we refer to as TR3D+FF, outperforms existing 3D object detection approaches on the SUN RGB-D dataset.

3D Object Detection Object +1

Top-Down Beats Bottom-Up in 3D Instance Segmentation

1 code implementation6 Feb 2023 Maksim Kolodiazhnyi, Anna Vorontsova, Anton Konushin, Danila Rukhovich

Most 3D instance segmentation methods exploit a bottom-up strategy, typically including resource-exhaustive post-processing.

Ranked #5 on 3D Instance Segmentation on S3DIS (using extra training data)

3D Instance Segmentation Segmentation +1

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

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

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

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

Contour-based Interactive Segmentation

no code implementations13 Feb 2023 Danil Galeev, Polina Popenova, Anna Vorontsova, Anton Konushin

Recent advances in interactive segmentation (IS) allow speeding up and simplifying image editing and labeling greatly.

Interactive Segmentation Segmentation

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

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

On the contrary, we propose GP$^{2}$, 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

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