Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Georg Kuschk"'
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031250552
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a6c0175a0e804eb92b637118d0e1f833
https://doi.org/10.1007/978-3-031-25056-9_44
https://doi.org/10.1007/978-3-031-25056-9_44
Publikováno v:
2022 19th European Radar Conference (EuRAD).
Publikováno v:
2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW).
Publikováno v:
ITSC
In this work, we solve the task of automotive traffic scene classification using a deep learning approach on low-level radar data. In contrast to existing approaches using 2D camera images, the input are complex-valued 3D range-beam-doppler tensors o
State-of-the-art scene flow algorithms pursue the conflicting targets of accuracy, run time, and robustness. With the successful concept of pixel-wise matching and sparse-to-dense interpolation, we push the limits of scene flow estimation. Avoiding s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::81279ad87e4f049e0720a126cdab9c35
http://arxiv.org/abs/1902.10099
http://arxiv.org/abs/1902.10099
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol II-3/W4, Pp 25-31 (2015)
Texture mapping techniques are used to achieve a high degree of realism for computer generated large-scale and detailed 3D surface models by extracting the texture information from photographic images and applying it to the object surfaces. Due to th
Publikováno v:
Intelligent Vehicles Symposium
We propose an algorithm for dense and direct large-scale visual SLAM that runs in real-time on a commodity notebook. A fast variational dense 3D reconstruction algorithm was developed which robustly integrates data terms from multiple images. This mi
In this paper, we propose an algorithm for robustly fusing digital surface models (DSMs) with different ground sampling distances and confidences, using explicit surface priors to obtain locally smooth surface models. Robust fusion of the DSMs is ach
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ee97858115cc66b3a86624cf41cfa5e1
https://elib.dlr.de/108351/
https://elib.dlr.de/108351/
Publikováno v:
WACV
While most scene flow methods use either variational optimization or a strong rigid motion assumption, we show for the first time that scene flow can also be estimated by dense interpolation of sparse matches. To this end, we find sparse matches acro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7f71d2f59a05cf2933f36e7e0ae085d3
Autor:
Pablo d'Angelo, Georg Kuschk
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XL-1/W3, Pp 247-251 (2013)
This paper proposes an algorithm for fusing digital surface models (DSM) obtained by heterogenous sensors. Based upon prior confidence knowledge, each DSM can be weighted locally adaptively and therefore strengthen or lessen its influence on the fuse