43 citations · 79 across the 6 of their papers we have counts for
9 papers
3DMOTFormer: Graph Transformer for Online 3D Multi-Object Tracking
Shuxiao Ding, Eike Rehder, Lukas Schneider +2
Tracking 3D objects accurately and consistently is crucial for autonomous vehicles, enabling more reliable downstream tasks such as trajectory prediction and motion planning. Based…
S.T.A.R.-Track: Latent Motion Models for End-to-End 3D Object Tracking with Adaptive Spatio-Temporal Appearance Representations
Simon Doll, Niklas Hanselmann, Lukas Schneider +3
Following the tracking-by-attention paradigm, this paper introduces an object-centric, transformer-based framework for tracking in 3D. Traditional model-based tracking approaches i…
Structural Knowledge Distillation for Object Detection
Philip de Rijk, Lukas Schneider, Marius Cordts +1
Knowledge Distillation (KD) is a well-known training paradigm in deep neural networks where knowledge acquired by a large teacher model is transferred to a small student. KD has pr…
Learning Stixel-based Instance Segmentation
Monty Santarossa, Lukas Schneider, Claudius Zelenka +3
Stixels have been successfully applied to a wide range of vision tasks in autonomous driving, recently including instance segmentation. However, due to their sparse occurrence in t…
Slanted Stixels: A way to represent steep streets
Daniel Hernandez-Juarez, Lukas Schneider, Pau Cebrian +6
This work presents and evaluates a novel compact scene representation based on Stixels that infers geometric and semantic information. Our approach overcomes the previous rather re…
Sparsity Invariant CNNs
Jonas Uhrig, Nick Schneider, Lukas Schneider +3
In this paper, we consider convolutional neural networks operating on sparse inputs with an application to depth upsampling from sparse laser scan data. First, we show that traditi…
Slanted Stixels: Representing San Francisco's Steepest Streets
Daniel Hernandez-Juarez, Lukas Schneider, Antonio Espinosa +5
In this work we present a novel compact scene representation based on Stixels that infers geometric and semantic information. Our approach overcomes the previous rather restrictive…
The Stixel world: A medium-level representation of traffic scenes
Marius Cordts, Timo Rehfeld, Lukas Schneider +5
Recent progress in advanced driver assistance systems and the race towards autonomous vehicles is mainly driven by two factors: (1) increasingly sophisticated algorithms that inter…
Semantically Guided Depth Upsampling
Nick Schneider, Lukas Schneider, Peter Pinggera +3
We present a novel method for accurate and efficient up- sampling of sparse depth data, guided by high-resolution imagery. Our approach goes beyond the use of intensity cues only a…