1 code implementation • 14 Oct 2022 • Adam Bielski, Paolo Favaro
We introduce MOVE, a novel method to segment objects without any form of supervision.
Ranked #2 on Unsupervised Saliency Detection on DUTS
no code implementations • 13 Jul 2021 • Abdelhak Lemkhenter, Adam Bielski, Alp Eren Sari, Paolo Favaro
We show a boost in the quality of generated samples with respect to FID from 10% to 40% compared to the baseline.
no code implementations • 7 Jul 2021 • Aram Davtyan, Sepehr Sameni, Llukman Cerkezi, Givi Meishvilli, Adam Bielski, Paolo Favaro
Moreover, we show that the Kalman Filter dynamical model for the evolution of the unknown parameters can be used to capture the gradient dynamics of advanced methods such as Momentum and Adam.
1 code implementation • NeurIPS 2019 • Adam Bielski, Paolo Favaro
To force the generator to learn a representation where the foreground layer corresponds to an object, we perturb the output of the generative model by introducing a random shift of both the foreground image and mask relative to the background.
no code implementations • 27 Apr 2018 • Adam Słucki, Tomasz Trzcinski, Adam Bielski, Paweł Cyrta
The main component of our system, i. e. the text recognition module, is inspired by a convolutional recurrent neural network architecture and we improve its performance using synthetically generated dataset of over 600, 000 images with text prepared by authors specifically for this task.
no code implementations • 26 Apr 2018 • Adam Bielski, Tomasz Trzcinski
Predicting popularity of social media videos before they are published is a challenging task, mainly due to the complexity of content distribution network as well as the number of factors that play part in this process.
no code implementations • 22 Apr 2018 • Ivona Tautkute, Tomasz Trzcinski, Adam Bielski
Classification of human emotions remains an important and challenging task for many computer vision algorithms, especially in the era of humanoid robots which coexist with humans in their everyday life.
no code implementations • 25 Jan 2018 • Tomasz Trzcinski, Adam Bielski, Paweł Cyrta, Matthew Zak
In this work, we present a comprehensive overview of machine learning-empowered tools we developed for video creators at Group Nine Media - one of the major social media companies that creates short-form videos with over three billion views per month.