1 code implementation • CVPR 2023 • Fengyi Shen, Akhil Gurram, Ziyuan Liu, He Wang, Alois Knoll
Domain adaptive semantic segmentation methods commonly utilize stage-wise training, consisting of a warm-up and a self-training stage.
no code implementations • 20 Feb 2023 • Akhil Gurram, Antonio M. Lopez
In particular, we take the task of 3D object detection on point clouds as a proxy of on-board perception.
1 code implementation • 21 Nov 2022 • Fengyi Shen, Zador Pataki, Akhil Gurram, Ziyuan Liu, He Wang, Alois Knoll
In this paper, we propose LoopDA for domain adaptive nighttime semantic segmentation.
1 code implementation • 30 Nov 2021 • Fengyi Shen, Akhil Gurram, Ahmet Faruk Tuna, Onay Urfalioglu, Alois Knoll
Due to the difficulty of obtaining ground-truth labels, learning from virtual-world datasets is of great interest for real-world applications like semantic segmentation.
1 code implementation • 22 Mar 2021 • Akhil Gurram, Ahmet Faruk Tuna, Fengyi Shen, Onay Urfalioglu, Antonio M. López
In this paper, we perform monocular depth estimation by virtual-world supervision (MonoDEVS) and real-world SfM self-supervision.
no code implementations • 7 Jun 2019 • Yi Xiao, Felipe Codevilla, Akhil Gurram, Onay Urfalioglu, Antonio M. López
On the other hand, we find end-to-end driving approaches that try to learn a direct mapping from input raw sensor data to vehicle control signals.
no code implementations • 21 Mar 2018 • Akhil Gurram, Onay Urfalioglu, Ibrahim Halfaoui, Fahd Bouzaraa, Antonio M. Lopez
Depth estimation provides essential information to perform autonomous driving and driver assistance.
Ranked #43 on Monocular Depth Estimation on KITTI Eigen split