3 citations · 8 across the 5 of their papers we have counts for
8 papers
Learning High-Resolution Domain-Specific Representations with a GAN Generator
Danil Galeev, Konstantin Sofiiuk, Danila Rukhovich +3
In recent years generative models of visual data have made a great progress, and now they are able to produce images of high quality and diversity. In this work we study representa…
IterDet: Iterative Scheme for Object Detection in Crowded Environments
Danila Rukhovich, Konstantin Sofiiuk, Danil Galeev +2
Deep learning-based detectors usually produce a redundant set of object bounding boxes including many duplicate detections of the same object. These boxes are then filtered using n…
f-BRS: Rethinking Backpropagating Refinement for Interactive Segmentation
Konstantin Sofiiuk, Ilia Petrov, Olga Barinova +1
Deep neural networks have become a mainstream approach to interactive segmentation. As we show in our experiments, while for some images a trained network provides accurate segment…
Training Deep SLAM on Single Frames
Igor Slinko, Anna Vorontsova, Dmitry Zhukov +2
Learning-based visual odometry and SLAM methods demonstrate a steady improvement over past years. However, collecting ground truth poses to train these methods is difficult and exp…
Measuring robustness of Visual SLAM
David Prokhorov, Dmitry Zhukov, Olga Barinova +2
Simultaneous localization and mapping (SLAM) is an essential component of robotic systems. In this work we perform a feasibility study of RGB-D SLAM for the task of indoor robot na…
DISCOMAN: Dataset of Indoor SCenes for Odometry, Mapping And Navigation
Pavel Kirsanov, Airat Gaskarov, Filipp Konokhov +7
We present a novel dataset for training and benchmarking semantic SLAM methods. The dataset consists of 200 long sequences, each one containing 3000-5000 data frames. We generate t…
AdaptIS: Adaptive Instance Selection Network
Konstantin Sofiiuk, Olga Barinova, Anton Konushin
We present Adaptive Instance Selection network architecture for class-agnostic instance segmentation. Given an input image and a point , it generates a mask for the object…
Scene Motion Decomposition for Learnable Visual Odometry
Igor Slinko, Anna Vorontsova, Filipp Konokhov +2
Optical Flow (OF) and depth are commonly used for visual odometry since they provide sufficient information about camera ego-motion in a rigid scene. We reformulate the problem of…