8 citations · 14 across the 6 of their papers we have counts for
7 papers
PoseDreamer: Scalable and Photorealistic Human Data Generation Pipeline with Diffusion Models
Lorenza Prospero, Orest Kupyn, Ostap Viniavskyi +2
Acquiring labeled datasets for 3D human mesh estimation is challenging due to depth ambiguities and the inherent difficulty of annotating 3D geometry from monocular images. Existin…
Self-Supervised Real-Time Tracking of Military Vehicles in Low-FPS UAV Footage
Markiyan Kostiv, Anatolii Adamovskyi, Yevhen Cherniavskyi +4
Multi-object tracking (MOT) aims to maintain consistent identities of objects across video frames. Associating objects in low-frame-rate videos captured by moving unmanned aerial v…
OpenGlue: Open Source Graph Neural Net Based Pipeline for Image Matching
Ostap Viniavskyi, Mariia Dobko, Dmytro Mishkin +1
We present OpenGlue: a free open-source framework for image matching, that uses a Graph Neural Network-based matcher inspired by SuperGlue \cite{sarlin20superglue}. We show that in…
Combining CNNs With Transformer for Multimodal 3D MRI Brain Tumor Segmentation With Self-Supervised Pretraining
Mariia Dobko, Danylo-Ivan Kolinko, Ostap Viniavskyi +1
We apply an ensemble of modified TransBTS, nnU-Net, and a combination of both for the segmentation task of the BraTS 2021 challenge. In fact, we change the original architecture of…
LID 2020: The Learning from Imperfect Data Challenge Results
Yunchao Wei, Shuai Zheng, Ming-Ming Cheng +32
Learning from imperfect data becomes an issue in many industrial applications after the research community has made profound progress in supervised learning from perfectly annotate…
Weakly-Supervised Segmentation for Disease Localization in Chest X-Ray Images
Ostap Viniavskyi, Mariia Dobko, Oles Dobosevych
Deep Convolutional Neural Networks have proven effective in solving the task of semantic segmentation. However, their efficiency heavily relies on the pixel-level annotations that…
NoPeopleAllowed: The Three-Step Approach to Weakly Supervised Semantic Segmentation
Mariia Dobko, Ostap Viniavskyi, Oles Dobosevych
We propose a novel approach to weakly supervised semantic segmentation, which consists of three consecutive steps. The first two steps extract high-quality pseudo masks from image-…