Zobrazeno 1 - 10
of 92
pro vyhledávání: '"Lis, Krzysztof"'
Vision transformers have emerged as powerful tools for many computer vision tasks. It has been shown that their features and class tokens can be used for salient object segmentation. However, the properties of segmentation transformers remain largely
Externí odkaz:
http://arxiv.org/abs/2212.14397
Publikováno v:
IEEE Robotics and Automation Letters ( Volume: 8, Issue: 4, April 2023, Pages: 2150-2157)
While road obstacle detection techniques have become increasingly effective, they typically ignore the fact that, in practice, the apparent size of the obstacles decreases as their distance to the vehicle increases. In this paper, we account for this
Externí odkaz:
http://arxiv.org/abs/2210.01779
Autor:
Fiedot, Marta, Junka, Adam, Brożyna, Malwina, Cybulska, Justyna, Zdunek, Artur, Kockova, Olga, Lis, Krzysztof, Chomiak, Katarzyna, Czajkowski, Maciej, Jędrzejewski, Roman, Szustakiewicz, Konrad, Cybińska, Joanna, Kennedy, John F.
Publikováno v:
In Carbohydrate Polymers 1 November 2024 343
Autor:
Chan, Robin, Lis, Krzysztof, Uhlemeyer, Svenja, Blum, Hermann, Honari, Sina, Siegwart, Roland, Fua, Pascal, Salzmann, Mathieu, Rottmann, Matthias
State-of-the-art semantic or instance segmentation deep neural networks (DNNs) are usually trained on a closed set of semantic classes. As such, they are ill-equipped to handle previously-unseen objects. However, detecting and localizing such objects
Externí odkaz:
http://arxiv.org/abs/2104.14812
Vehicles can encounter a myriad of obstacles on the road, and it is impossible to record them all beforehand to train a detector. Instead, we select image patches and inpaint them with the surrounding road texture, which tends to remove obstacles fro
Externí odkaz:
http://arxiv.org/abs/2012.13633
Autor:
Fua, Pascal, Lis, Krzysztof
Python currently is the dominant language in the field of Machine Learning but is often criticized for being slow to perform certain tasks. In this report, we use the well-known $N$-queens puzzle as a benchmark to show that once compiled using the Nu
Externí odkaz:
http://arxiv.org/abs/2001.02491
Classical semantic segmentation methods, including the recent deep learning ones, assume that all classes observed at test time have been seen during training. In this paper, we tackle the more realistic scenario where unexpected objects of unknown c
Externí odkaz:
http://arxiv.org/abs/1904.07595
Akademický článek
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Autor:
Melnychenko, Anna M., Zelewski, Szymon J., Hlushchenko, Daria, Lis, Krzysztof, Bachmatiuk, Alicja, Kudrawiec, Robert
Publikováno v:
In Applied Surface Science 15 March 2023 613
State-of-the-art methods for counting people in crowded scenes rely on deep networks to estimate crowd density in the image plane. While useful for this purpose, this image-plane density has no immediate physical meaning because it is subject to pers
Externí odkaz:
http://arxiv.org/abs/1803.08805