114 citations · 136 across the 5 of their papers we have counts for
5 papers
Co-Training for Unsupervised Domain Adaptation of Semantic Segmentation Models
Jose L. Gómez, Gabriel Villalonga, Antonio M. López
Semantic image segmentation is a central and challenging task in autonomous driving, addressed by training deep models. Since this training draws to a curse of human-based image la…
Co-training for Deep Object Detection: Comparing Single-modal and Multi-modal Approaches
Jose L. Gómez, Gabriel Villalonga, Antonio M. López
Top-performing computer vision models are powered by convolutional neural networks (CNNs). Training an accurate CNN highly depends on both the raw sensor data and their associated…
Monocular Depth Estimation through Virtual-world Supervision and Real-world SfM Self-Supervision
Akhil Gurram, Ahmet Faruk Tuna, Fengyi Shen +2
Depth information is essential for on-board perception in autonomous driving and driver assistance. Monocular depth estimation (MDE) is very appealing since it allows for appearanc…
Variable Rate Deep Image Compression with Modulated Autoencoder
Fei Yang, Luis Herranz, Joost van de Weijer +3
Variable rate is a requirement for flexible and adaptable image and video compression. However, deep image compression methods are optimized for a single fixed rate-distortion trad…
Training a Binary Weight Object Detector by Knowledge Transfer for Autonomous Driving
Jiaolong Xu, Peng Wang, Heng Yang +1
Autonomous driving has harsh requirements of small model size and energy efficiency, in order to enable the embedded system to achieve real-time on-board object detection. Recent d…