no code implementations • 7 Nov 2023 • Ugur Sahin, Hang Li, Qadeer Khan, Daniel Cremers, Volker Tresp
Leveraging these generative hard negative samples, we significantly enhance VLMs' performance in tasks involving multimodal compositional reasoning.
no code implementations • 16 Aug 2023 • Jiaxin Pan, Changyao Zhou, Mariia Gladkova, Qadeer Khan, Daniel Cremers
In this work, we present a learning method for lateral and longitudinal motion control of an ego-vehicle for vehicle pursuit.
1 code implementation • 2 Aug 2023 • Jonathan Schmidt, Qadeer Khan, Daniel Cremers
We train a deep learning model, which takes a LiDAR scan as input and predicts the future trajectory as output.
1 code implementation • 6 Jan 2023 • Dekai Zhu, Qadeer Khan, Daniel Cremers
This is done by training a neural network which takes the state and intent of the multiple vehicles to predict their future trajectory.
1 code implementation • 13 Jun 2022 • Hang Li, Qadeer Khan, Volker Tresp, Daniel Cremers
The human brain can be considered to be a graphical structure comprising of tens of billions of biological neurons connected by synapses.
no code implementations • 20 Mar 2022 • Florian Müller, Qadeer Khan, Daniel Cremers
In this paper, a framework for training a more robust and scalable model for lateral vehicle control is proposed.
no code implementations • 20 Mar 2021 • Qadeer Khan, Patrick Wenzel, Daniel Cremers
Vision-based learning methods for self-driving cars have primarily used supervised approaches that require a large number of labels for training.
no code implementations • 14 Sep 2020 • Patrick Wenzel, Rui Wang, Nan Yang, Qing Cheng, Qadeer Khan, Lukas von Stumberg, Niclas Zeller, Daniel Cremers
We present a novel dataset covering seasonal and challenging perceptual conditions for autonomous driving.
no code implementations • 25 Jul 2019 • Qadeer Khan, Patrick Wenzel, Daniel Cremers, Laura Leal-Taixé
The ability of deep learning models to generalize well across different scenarios depends primarily on the quality and quantity of annotated data.
1 code implementation • 26 Apr 2019 • Lukas von Stumberg, Patrick Wenzel, Qadeer Khan, Daniel Cremers
Direct SLAM methods have shown exceptional performance on odometry tasks.
no code implementations • 12 Feb 2019 • Qadeer Khan, Torsten Schön, Patrick Wenzel
In this paper, we present a framework to control a self-driving car by fusing raw information from RGB images and depth maps.
no code implementations • 11 Feb 2019 • Qadeer Khan, Torsten Schön, Patrick Wenzel
The control module trained with reinforcement learning takes the latent vector as input to predict the correct steering angle.
no code implementations • 11 Feb 2019 • Qadeer Khan, Torsten Schön, Patrick Wenzel
Semantic segmentation maps can be used as input to models for maneuvering the controls of a car.
1 code implementation • 3 Jul 2018 • Patrick Wenzel, Qadeer Khan, Daniel Cremers, Laura Leal-Taixé
To this end, we propose to divide the task of vehicle control into two independent modules: a control module which is only trained on one weather condition for which labeled steering data is available, and a perception module which is used as an interface between new weather conditions and the fixed control module.