Publications
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ReVLA: Reverting Visual Domain Limitation of Robotic Foundation Models
Sombit Dey, Jan-Nico Zaech, Nikolay Nikolov, Luc Van Gool, Danda Pani Paudel International Conference on Robotics and Automation, ICRA 2025 Abstract Recent progress in large language models and access to large-scale robotic datasets has sparked a paradigm shift in robotics models transforming them into generalists able to adapt to various tasks, scenes, and robot modalities.…
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Occam’s LGS: An Efficient Approach for Language Gaussian Splatting
Jiahuan Cheng, Jan-Nico Zaech, Luc Van Gool, Danda Pani Paudel Gaussian Splatting is a widely adopted approach for 3D scene representation, offering efficient, high-quality reconstruction and rendering. A key reason for its success is the simplicity of representing scenes with sets of Gaussians, making it interpretable and adaptable. To enhance understanding beyond visual representation, recent…
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Holistic Understanding of 3D Scenes as Universal Scene Description
Anna-Maria Halacheva, Yang Miao, Jan-Nico Zaech, Xi Wang, Luc Van Gool, Danda Pani Paudel 3D scene understanding is a long-standing challenge in computer vision and a key component in enabling mixed reality, wearable computing, and embodied AI. Providing a solution to these applications requires a multifaceted approach that covers scene-centric, object-centric, as well as interaction-centric…
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Probabilistic Sampling of Balanced K-Means using Adiabatic Quantum Computing
Jan-Nico Zaech, Martin Danelljan, Tolga Birdal, Luc Van Gool IEEE Conference on Computer Vision and Pattern Recognition 2024 (CVPR) Abstract Adiabatic quantum computing (AQC) is a promising approach for discrete and often NP-hard optimization problems. Current AQCs allow to implement problems of research interest, which has sparked the development of quantum representations for many computer…
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Optimizing Long-Term Player Tracking and Identification in NAO Robot Soccer by fusing Game-state and External Video
A collaborative sensing approach for multi object tracking of robots.
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Adiabatic Quantum Computing for Multi Object Tracking
A Multi-Object Tracking algorithm that can be solved with Adiabatic Quantum Computing
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Learnable Online Graph Representations for 3D Multi-Object Tracking
An online 3D Multi-Object Tracking method based on graph neural networks.
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Unsupervised robust domain adaptation without source data
A method that keeps a network robust against adversarial images during source-free domain adaptation.
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Decoder fusion RNN: Context and interaction aware decoders for trajectory prediction
A multi-headed attention based method for vehicle trajectory prediction using map data encoded on a graph.
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Action sequence predictions of vehicles in urban environments using map and social context
Views the traffic agent trajectory prediction task form a classification perspective and proposes a method to automatically annotate trajectory data by using graph-based maps.