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 #3 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
2 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 #4 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 #1 on
Monocular 3D Object Detection
on SUN RGB-D
1 code implementation • 18 Jun 2020 • Danil Galeev, Konstantin Sofiiuk, Danila Rukhovich, Mikhail Romanov, Olga Barinova, Anton Konushin
Based on this finding, we propose LayerMatch scheme for approximating the representation of a GAN generator that can be used for unsupervised domain-specific pretraining.
Semi-Supervised Semantic Segmentation
Vocal Bursts Intensity Prediction
1 code implementation • 12 May 2020 • Danila Rukhovich, Konstantin Sofiiuk, Danil Galeev, Olga Barinova, Anton Konushin
Deep learning-based detectors usually produce a redundant set of object bounding boxes including many duplicate detections of the same object.
Ranked #1 on
Object Detection
on WiderPerson
1 code implementation • 9 Oct 2019 • Danila Rukhovich, Danil Galeev
We present a domain adaptation (DA) system that can be used in multi-source and semi-supervised settings.
no code implementations • 2 Sep 2019 • Danila Rukhovich, Daniel Mouritzen, Ralf Kaestner, Martin Rufli, Alexander Velizhev
This paper addresses the problem of scale estimation in monocular SLAM by estimating absolute distances between camera centers of consecutive image frames.