18 citations · 21 across the 5 of their papers we have counts for
5 papers
PO-GUISE+: Pose and object guided transformer token selection for efficient driver action recognition
Ricardo Pizarro, Roberto Valle, Rafael Barea +3
We address the task of identifying distracted driving by analyzing in-car videos using efficient transformers. Although transformer models have achieved outstanding performance in…
Efficient Baselines for Motion Prediction in Autonomous Driving
Carlos Gómez-Huélamo, Marcos V. Conde, Rafael Barea +2
Motion Prediction (MP) of multiple surroundings agents is a crucial task in arbitrarily complex environments, from simple robots to Autonomous Driving Stacks (ADS). Current techniq…
S-MonoDETR: Supervised Shape&Scale-perceptive Deformable Transformer for Monocular 3D Object Detection
Xuan He, Jin Yuan, Kailun Yang +2
Recently, transformer-based methods have shown exceptional performance in monocular 3D object detection, which can predict 3D attributes from a single 2D image. These methods typic…
Exploring Attention GAN for Vehicle Motion Prediction
Carlos Gómez-Huélamo, Marcos V. Conde, Miguel Ortiz +3
The design of a safe and reliable Autonomous Driving stack (ADS) is one of the most challenging tasks of our era. These ADS are expected to be driven in highly dynamic environments…
Can we unify monocular detectors for autonomous driving by using the pixel-wise semantic segmentation of CNNs?
Eduardo Romera, Luis M. Bergasa, Roberto Arroyo
Autonomous driving is a challenging topic that requires complex solutions in perception tasks such as recognition of road, lanes, traffic signs or lights, vehicles and pedestrians.…