35 citations · 78 across the 9 of their papers we have counts for
4 papers · 1 filter
Semi-Supervised Diversity-Aware Domain Adaptation for 3D Object detection
Bartłomiej Olber, Jakub Winter, Paweł Wawrzyński +5
3D object detectors are fundamental components of perception systems in autonomous vehicles. While these detectors achieve remarkable performance on standard autonomous driving ben…
Detecting Out-of-distribution Objects Using Neuron Activation Patterns
Bartłomiej Olber, Krystian Radlak, Krystian Chachuła +2
Object detection is essential to many perception algorithms used in modern robotics applications. Unfortunately, the existing models share a tendency to assign high confidence scor…
Combating noisy labels in object detection datasets
Krystian Chachuła, Jakub Łyskawa, Bartłomiej Olber +3
The quality of training datasets for deep neural networks is a key factor contributing to the accuracy of resulting models. This effect is amplified in difficult tasks such as obje…
Deep Learning based Switching Filter for Impulsive Noise Removal in Color Images
Krystian Radlak, Lukasz Malinski, Bogdan Smolka
Noise reduction is one the most important and still active research topic in low-level image processing due to its high impact on object detection and scene understanding for compu…