549 citations · 1.5k across the 32 of their papers we have counts for
8 papers · 1 filter
End-to-End Learning of Multi-category 3D Pose and Shape Estimation
Yigit Baran Can, Alexander Liniger, Danda Pani Paudel +1
In this paper, we study the representation of the shape and pose of objects using their keypoints. Therefore, we propose an end-to-end method that simultaneously detects 2D keypoin…
Topology Preserving Local Road Network Estimation from Single Onboard Camera Image
Yigit Baran Can, Alexander Liniger, Danda Pani Paudel +1
Knowledge of the road network topology is crucial for autonomous planning and navigation. Yet, recovering such topology from a single image has only been explored in part. Furtherm…
Structured Bird's-Eye-View Traffic Scene Understanding from Onboard Images
Yigit Baran Can, Alexander Liniger, Danda Pani Paudel +1
Autonomous navigation requires structured representation of the road network and instance-wise identification of the other traffic agents. Since the traffic scene is defined on the…
Decoder Fusion RNN: Context and Interaction Aware Decoders for Trajectory Prediction
Edoardo Mello Rella, Jan-Nico Zaech, Alexander Liniger +1
Forecasting the future behavior of all traffic agents in the vicinity is a key task to achieve safe and reliable autonomous driving systems. It is a challenging problem as agents a…
End-to-End Urban Driving by Imitating a Reinforcement Learning Coach
Zhejun Zhang, Alexander Liniger, Dengxin Dai +2
End-to-end approaches to autonomous driving commonly rely on expert demonstrations. Although humans are good drivers, they are not good coaches for end-to-end algorithms that deman…
Learnable Online Graph Representations for 3D Multi-Object Tracking
Jan-Nico Zaech, Dengxin Dai, Alexander Liniger +2
Tracking of objects in 3D is a fundamental task in computer vision that finds use in a wide range of applications such as autonomous driving, robotics or augmented reality. Most re…
Spectral Tensor Train Parameterization of Deep Learning Layers
Anton Obukhov, Maxim Rakhuba, Alexander Liniger +4
We study low-rank parameterizations of weight matrices with embedded spectral properties in the Deep Learning context. The low-rank property leads to parameter efficiency and permi…
A Holistic Motion Planning and Control Solution to Challenge a Professional Racecar Driver
Sirish Srinivasan, Sebastian Nicolas Giles, Alexander Liniger
We present a holistically designed three layer control architecture capable of outperforming a professional driver racing the same car. Our approach focuses on the co-design of the…