4 citations · 4 across the 4 of their papers we have counts for
6 papers · 1 filter
Comprehensive Robustness Analysis of LiDAR-based 3D Object Detection in Autonomous Driving
Adwait Chandorkar, Kai Krink, Yerdana Maulenbay +2
Recent advancements in LiDAR-only 3D object detection have demonstrated improved detection accuracy over benchmark datasets. However, the adversarial robustness of these models rem…
Graph Query Networks for Object Detection with Automotive Radar
Loveneet Saini, Hasan Tercan, Tobias Meisen
Object detection with 3D radar is essential for 360-degree automotive perception, but radar's long wavelengths produce sparse and irregular reflections that challenge traditional g…
Rethinking Backbone Design for Lightweight 3D Object Detection in LiDAR
Adwait Chandorkar, Hasan Tercan, Tobias Meisen
Recent advancements in LiDAR-based 3D object detection have significantly accelerated progress toward the realization of fully autonomous driving in real-world environments. Despit…
Efficient Inter-Task Attention for Multitask Transformer Models
Christian Bohn, Thomas Kurbiel, Klaus Friedrichs +2
In both Computer Vision and the wider Deep Learning field, the Transformer architecture is well-established as state-of-the-art for many applications. For Multitask Learning, howev…
Detection Transformers Under the Knife: A Neuroscience-Inspired Approach to Ablations
Nils Hütten, Florian Hölken, Hasan Tercan +1
In recent years, Explainable AI has gained traction as an approach to enhancing model interpretability and transparency, particularly in complex models such as detection transforme…
AttentiveGRU: Recurrent Spatio-Temporal Modeling for Advanced Radar-Based BEV Object Detection
Loveneet Saini, Mirko Meuter, Hasan Tercan +1
Bird's-eye view (BEV) object detection has become important for advanced automotive 3D radar-based perception systems. However, the inherently sparse and non-deterministic nature o…