Seznam |
Téma: | Deep learning for dense reconstruction from sparse depth measurements and RGB images |
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Vedoucí: | doc. Ing. Karel Zimmermann Ph.D. |
Vypsáno jako: | Diplomová práce,Bakalářská práce,Individuální projekt,Dobrovolná odborná práce,Semestrální projektPráce v týmu a její organizace |
Popis: | Accurate 3D perception is an essential component for many fundamental capabilities such as emergency braking, predictive control for active damping, safe turning on a road intersection or self-localization from offline maps. Consequently, any fully-autonomous vehicle requires a sensor (e.g. Velodyne) providing high resolution and long range 3D measurements. The high resolution sensors are expensive, heavy, slow, and prone to mechanical wear, therefore low-resolution depth sensors (e.g. with only 4 row measurements planes) are often used in contemporary semi-autonomous cars. Autonomous estimation of high-resolution depth data from such sparse depth-measurements fused with RGB images seems to be a viable option for a close future. Learn a deep convolution neural network for dense depth reconstruction, given dataset (provided by thesis supervisor) captured by an autonomous car with calibrated (i) Velodyne sensor, (ii) cheap sparse depth-sensor and (iii) RGB camera.
Preffered qualification: - B or better result achieved in a programming oriented subject or even better: the active participation in a programming competition (e.g. CTU Open Contest, ACM ICPC). - B or better result achieved in a computer vision oriented subject. - experience with Python and Tensorflow - good mathemathical background. supervisor's web: http://cmp.felk.cvut.cz/~zimmerk/ |
Pokyny: | (1) Study state-of-the-art methods such as [1,2].
(2) Propose and implement you own algorithm. (3) Evaluate proposed method on a selected dataset such as [3]. |
Literatura: | [1] Jiwon Kim, Jung Kwon Lee and Kyoung Mu Lee, 'Accurate Image Super-Resolution Using Very Deep Convolutional Networks', CVPR oral, 2016. http://cv.snu.ac.kr/research/VDSR/ [2] https://github.com/flyywh/Video-Super-Resolution [3] http://www.cvlibs.net/datasets/kitti/ |
Vypsáno dne: | 10.10.2017 |
Max. počet studentů: | 6 |
Přihlášení studenti: | Dmitrii Noskov |