no code implementations • 9 Feb 2024 • Andrey Moskalenko, Vlad Shakhuro, Anna Vorontsova, Anton Konushin, Anton Antonov, Alexander Krapukhin, Denis Shepelev, Konstantin Soshin
Based on the performance with such adversarial user inputs, we assess the robustness of interactive segmentation models w. r. t click positions.
1 code implementation • 24 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.
Ranked #1 on Panoptic Segmentation on ScanNet
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.
no code implementations • 13 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.
1 code implementation • 6 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)
1 code implementation • 6 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.
Ranked #2 on 3D Object Detection on SUN-RGBD val
no code implementations • 10 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.
3 code implementations • 1 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.
Ranked #5 on 3D Object Detection on S3DIS
3 code implementations • 2 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.
Ranked #2 on Monocular 3D Object Detection on SUN RGB-D
Monocular 3D Object Detection Monocular 3D Object Detection (10 / NYU-37) +4
1 code implementation • 25 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.
1 code implementation • 11 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.
no code implementations • 10 Oct 2019 • David Prokhorov, Dmitry Zhukov, Olga Barinova, Anna Vorontsova, Anton Konushin
We find that while in many cases the accuracy of SLAM is very good, the robustness is still an issue.
no code implementations • 26 Sep 2019 • Pavel Kirsanov, Airat Gaskarov, Filipp Konokhov, Konstantin Sofiiuk, Anna Vorontsova, Igor Slinko, Dmitry Zhukov, Sergey Bykov, Olga Barinova, Anton Konushin
We present a novel dataset for training and benchmarking semantic SLAM methods.
no code implementations • 16 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.