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Driving with LLMs: Fusing Object-Level Vector Modality for Explainable Autonomous Driving
Large Language Models (LLMs) have shown promise in the autonomous driving sector, particularly in generalization and interpretability. …
Long Chen, Oleg Sinavski, Jan Hünermann, Alice Karnsund, Andrew James Willmott, Danny Birch, Daniel Maund, Jamie Shotton
May, 2023 In arXiv preprint arXiv:2310.01957
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Driving with LLMs: Fusing Object-Level Vector Modality for Explainable Autonomous Driving
One Thousand and One Hours: Self-driving Motion Prediction Dataset
Motivated by the impact of large-scale datasets on ML systems we present the largest self-driving dataset for motion prediction to …
John Houston, Guido Zuidhof, Luca Bergamini, Yawei Ye, Long Chen, Ashesh Jain, Sammy Omari, Vladimir Iglovikov, Peter Ondruska
November, 2021 In Proceedings of the 2020 Conference on Robot Learning (CoRL)
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One Thousand and One Hours: Self-driving Motion Prediction Dataset
Guided Batching: a method for building city-scale HD maps from limited field-of-view cameras
The present invention provides a method of generating a robust global map using a plurality of limited field-of-view cameras to capture …
Long Chen, Benjamin Alex Haines, Luca Del Pero
February, 2021 US Patnet - US10914605B1
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Guided Batching: a method for building city-scale HD maps from limited field-of-view cameras
SimNet: Learning reactive self-driving simulations from real-world observations
In this work, we present a simple end-to-end trainable machine learning system capable of realistically simulating driving experiences. …
Luca Bergamini, Yawei Ye, Oliver Scheel, Long Chen, Chih Hu, Luca Del Pero, Błażej Osiński, Hugo Grimmett, Peter Ondruska
January, 2021 In 2021 IEEE International Conference on Robotics and Automation (ICRA)
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SimNet: Learning reactive self-driving simulations from real-world observations
What data do we need for training an av motion planner?
We investigate what grade of sensor data is required for training an imitation-learning-based AV planner on human expert demonstration. …
Long Chen, Lukas Platinsky, Stefanie Speichert, Błażej Osiński, Oliver Scheel, Yawei Ye, Hugo Grimmett, Luca Del Pero, Peter Ondruska
January, 2021 In 2021 IEEE International Conference on Robotics and Automation (ICRA)
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What data do we need for training an av motion planner?
Context-Aware Mixed Reality: A Learning-Based Framework for Semantic-Level Interaction
Mixed reality (MR) is a powerful interactive technology for new types of user experience. We present a semantic-based interactive MR …
Long Chen, Wen Tang, Nigel W. John, Tao Ruan Wan, Jian Jun Zhang
January, 2020 In Computer Graphics Forum
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Context-Aware Mixed Reality: A Learning-Based Framework for Semantic-Level Interaction
Self-supervised monocular image depth learning and confidence estimation
We present a novel self-supervised framework for monocular image depth learning and confidence estimation. Our framework reduces the …
Long Chen, Wen Tang, Nigel W John
January, 2020 In Neurocomputing
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Self-supervised monocular image depth learning and confidence estimation
De-smokeGCN: generative cooperative networks for joint surgical smoke detection and removal
Surgical smoke removal algorithms can improve the quality of intra-operative imaging and reduce hazards in image-guided surgery, a …
Long Chen, Wen Tang, Nigel W John, Tao Ruan Wan, Jian Jun Zhang
January, 2019 In IEEE Transactions on Medical Imaging
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De-smokeGCN: generative cooperative networks for joint surgical smoke detection and removal
SLAM-based dense surface reconstruction in monocular minimally invasive surgery and its application to augmented reality
Background and objective: While Minimally Invasive Surgery (MIS) offers considerable benefits to patients, it also imposes big …
Long Chen, Wen Tang, Nigel W John, Tao Ruan Wan, Jian Jun Zhang
January, 2018 In Computer Methods and Programs in Biomedicine
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SLAM-based dense surface reconstruction in monocular minimally invasive surgery and its application to augmented reality
Recent Developments and Future Challenges in Medical Mixed Reality
Mixed Reality (MR) is of increasing interest within technology-driven modern medicine but is not yet used in everyday practice. This …
Long Chen, Thomas Day, Wen Tang, Nigel W John
August, 2017 In The 16th IEEE International Symposium on Mixed and Augmented Reality (ISMAR)
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Recent Developments and Future Challenges in Medical Mixed Reality