activity
20222026
most citedKnowledge Augmented Machine Learning with Applications in Autonomous Driving: A Survey

14 citations · 19 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CV2026

Recall to Predict: Grounding Motion Forecasting in Interpretable Motion Bank

Abhishek Vivekanandan, Ahmed Abouelazm, J. Marius Zöllner

Motion forecasting often requires trading interpretability for predictive accuracy. Standard anchor-based architectures rely on opaque latent queries that are highly prone to laten…

cs.CV2025

Contrast & Compress: Learning Lightweight Embeddings for Short Trajectories

Abhishek Vivekanandan, Christian Hubschneider, J. Marius Zöllner

The ability to retrieve semantically and directionally similar short-range trajectories with both accuracy and efficiency is foundational for downstream applications such as motion…

cs.CV2025★ 1 cited

Generative AI for Autonomous Driving: A Review

Katharina Winter, Abhishek Vivekanandan, Rupert Polley +17

Generative AI (GenAI) is rapidly advancing the field of Autonomous Driving (AD), extending beyond traditional applications in text, image, and video generation. We explore how gene…

cs.CV2025

RetroMotion: Retrocausal Motion Forecasting Models are Instructable

Royden Wagner, Omer Sahin Tas, Felix Hauser +7

Motion forecasts of road users (i.e., agents) vary in complexity depending on the number of agents, scene constraints, and interactions. In particular, the output space of joint tr…

cs.RO2024

Empowering Autonomous Shuttles with Next-Generation Infrastructure

Sven Ochs, Melih Yazgan, Rupert Polley +9

As cities strive to address urban mobility challenges, combining autonomous transportation technologies with intelligent infrastructure presents an opportunity to transform how peo…

cs.CV2024

Efficient Data Representation for Motion Forecasting: A Scene-Specific Trajectory Set Approach

Abhishek Vivekanandan, J. Marius Zöllner

Representing diverse and plausible future trajectories is critical for motion forecasting in autonomous driving. However, efficiently capturing these trajectories in a compact set…

cs.RO2023★ 4 cited

KI-PMF: Knowledge Integrated Plausible Motion Forecasting

Abhishek Vivekanandan, Ahmed Abouelazm, Philip Schörner +1

Accurately forecasting the motion of traffic actors is crucial for the deployment of autonomous vehicles at a large scale. Current trajectory forecasting approaches primarily conce…

cs.CV2022

Plausibility Verification For 3D Object Detectors Using Energy-Based Optimization

Abhishek Vivekanandan, Niels Maier, J. Marius Zoellner

Environmental perception obtained via object detectors have no predictable safety layer encoded into their model schema, which creates the question of trustworthiness about the sys…

cs.LG2022★ 14 cited

Knowledge Augmented Machine Learning with Applications in Autonomous Driving: A Survey

Julian Wörmann, Daniel Bogdoll, Christian Brunner +49

The availability of representative datasets is an essential prerequisite for many successful artificial intelligence and machine learning models. However, in real life applications…