Dr Li Li
PhD (Co-supervised with Prof. Toby P. Breckon)
, 2020 - 2024
Durham University
, UK
- Research topic: Computer vision for self-driving cars
- Examiners: Dr Oisin Mac Aodha, Dr Amir Atapour-Abarghouei
Publications with the Team
TFDM: Time-Variant Frequency-Based Point Cloud Diffusion with Mamba
arXiv Preprint, 2025
Jiaxu Liu, Li Li, Hubert P. H. Shum and Toby P. Breckon
Topics:
Webpage Cite This Plain Text
arXiv Preprint, 2025
Jiaxu Liu, Li Li, Hubert P. H. Shum and Toby P. Breckon
Topics:
Webpage Cite This Plain Text
Jiaxu Liu, Li Li, Hubert P. H. Shum and Toby P. Breckon, "TFDM: Time-Variant Frequency-Based Point Cloud Diffusion with Mamba," arXiv preprint arXiv:2503.13004, 2025.
Bibtex @article{liu24tfdm,
author={Liu, Jiaxu and Li, Li and Shum, Hubert P. H. and Breckon, Toby P.},
journal={arXiv},
title={TFDM: Time-Variant Frequency-Based Point Cloud Diffusion with Mamba},
year={2025},
numpages={10},
eprint={arXiv:2503.13004},
archivePrefix={arXiv},
primaryClass={cs.CV},
doi={10.48550/arXiv.2503.13004},
url={https://arxiv.org/abs/2503.13004},
}
RIS author={Liu, Jiaxu and Li, Li and Shum, Hubert P. H. and Breckon, Toby P.},
journal={arXiv},
title={TFDM: Time-Variant Frequency-Based Point Cloud Diffusion with Mamba},
year={2025},
numpages={10},
eprint={arXiv:2503.13004},
archivePrefix={arXiv},
primaryClass={cs.CV},
doi={10.48550/arXiv.2503.13004},
url={https://arxiv.org/abs/2503.13004},
}
TY - Preprint
AU - Liu, Jiaxu
AU - Li, Li
AU - Shum, Hubert P. H.
AU - Breckon, Toby P.
JO - arXiv preprints
SP - arXiv:2503.13004
KW - cs.CV
TI - TFDM: Time-Variant Frequency-Based Point Cloud Diffusion with Mamba
PY - 2025
DO - 10.48550/arXiv.2503.13004
ER -
AU - Liu, Jiaxu
AU - Li, Li
AU - Shum, Hubert P. H.
AU - Breckon, Toby P.
JO - arXiv preprints
SP - arXiv:2503.13004
KW - cs.CV
TI - TFDM: Time-Variant Frequency-Based Point Cloud Diffusion with Mamba
PY - 2025
DO - 10.48550/arXiv.2503.13004
ER -
RAPiD-Seg: Range-Aware Pointwise Distance Distribution Networks for 3D LiDAR Segmentation Oral Paper (Top 2.3% of 8585 Submissions) H5-Index: 206# Core A* Conference‡
Proceedings of the 2024 European Conference on Computer Vision (ECCV), 2024
Li Li, Hubert P. H. Shum and Toby P. Breckon
Topics: Environment Sensing
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Proceedings of the 2024 European Conference on Computer Vision (ECCV), 2024
Li Li, Hubert P. H. Shum and Toby P. Breckon
Topics: Environment Sensing
Webpage Cite This Plain Text
Li Li, Hubert P. H. Shum and Toby P. Breckon, "RAPiD-Seg: Range-Aware Pointwise Distance Distribution Networks for 3D LiDAR Segmentation," in ECCV '24: Proceedings of the 2024 European Conference on Computer Vision, vol. 15065, pp. 222-241, Milan, Italy, Springer, 2024.
Bibtex @inproceedings{li24rapidseg,
author={Li, Li and Shum, Hubert P. H. and Breckon, Toby P.},
booktitle={Proceedings of the 2024 European Conference on Computer Vision},
series={ECCV '24},
title={RAPiD-Seg: Range-Aware Pointwise Distance Distribution Networks for 3D LiDAR Segmentation},
year={2024},
volume={15065},
pages={222--241},
numpages={20},
doi={10.1007/978-3-031-72667-5_13},
publisher={Springer},
location={Milan, Italy},
}
RIS author={Li, Li and Shum, Hubert P. H. and Breckon, Toby P.},
booktitle={Proceedings of the 2024 European Conference on Computer Vision},
series={ECCV '24},
title={RAPiD-Seg: Range-Aware Pointwise Distance Distribution Networks for 3D LiDAR Segmentation},
year={2024},
volume={15065},
pages={222--241},
numpages={20},
doi={10.1007/978-3-031-72667-5_13},
publisher={Springer},
location={Milan, Italy},
}
TY - CONF
AU - Li, Li
AU - Shum, Hubert P. H.
AU - Breckon, Toby P.
T2 - Proceedings of the 2024 European Conference on Computer Vision
TI - RAPiD-Seg: Range-Aware Pointwise Distance Distribution Networks for 3D LiDAR Segmentation
PY - 2024
VL - 15065
SP - 222
EP - 241
DO - 10.1007/978-3-031-72667-5_13
PB - Springer
ER -
Paper Supplementary Material YouTube Part 1 YouTube Part 2AU - Li, Li
AU - Shum, Hubert P. H.
AU - Breckon, Toby P.
T2 - Proceedings of the 2024 European Conference on Computer Vision
TI - RAPiD-Seg: Range-Aware Pointwise Distance Distribution Networks for 3D LiDAR Segmentation
PY - 2024
VL - 15065
SP - 222
EP - 241
DO - 10.1007/978-3-031-72667-5_13
PB - Springer
ER -
TraIL-Det: Transformation-Invariant Local Feature Networks for 3D LiDAR Object Detection with Unsupervised Pre-Training H5-Index: 65#
Proceedings of the 2024 British Machine Vision Conference (BMVC), 2024
Li Li, Tanqiu Qiao, Hubert P. H. Shum and Toby P. Breckon
Topics: Environment Sensing
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Proceedings of the 2024 British Machine Vision Conference (BMVC), 2024
Li Li, Tanqiu Qiao, Hubert P. H. Shum and Toby P. Breckon
Topics: Environment Sensing
Webpage Cite This Plain Text
Li Li, Tanqiu Qiao, Hubert P. H. Shum and Toby P. Breckon, "TraIL-Det: Transformation-Invariant Local Feature Networks for 3D LiDAR Object Detection with Unsupervised Pre-Training," in BMVC '24: Proceedings of the 2024 British Machine Vision Conference, Glasgow, UK, 2024.
Bibtex @inproceedings{li24traildet,
author={Li, Li and Qiao, Tanqiu and Shum, Hubert P. H. and Breckon, Toby P.},
booktitle={Proceedings of the 2024 British Machine Vision Conference},
series={BMVC '24},
title={TraIL-Det: Transformation-Invariant Local Feature Networks for 3D LiDAR Object Detection with Unsupervised Pre-Training},
year={2024},
location={Glasgow, UK},
}
RIS author={Li, Li and Qiao, Tanqiu and Shum, Hubert P. H. and Breckon, Toby P.},
booktitle={Proceedings of the 2024 British Machine Vision Conference},
series={BMVC '24},
title={TraIL-Det: Transformation-Invariant Local Feature Networks for 3D LiDAR Object Detection with Unsupervised Pre-Training},
year={2024},
location={Glasgow, UK},
}
TY - CONF
AU - Li, Li
AU - Qiao, Tanqiu
AU - Shum, Hubert P. H.
AU - Breckon, Toby P.
T2 - Proceedings of the 2024 British Machine Vision Conference
TI - TraIL-Det: Transformation-Invariant Local Feature Networks for 3D LiDAR Object Detection with Unsupervised Pre-Training
PY - 2024
ER -
Paper Supplementary MaterialAU - Li, Li
AU - Qiao, Tanqiu
AU - Shum, Hubert P. H.
AU - Breckon, Toby P.
T2 - Proceedings of the 2024 British Machine Vision Conference
TI - TraIL-Det: Transformation-Invariant Local Feature Networks for 3D LiDAR Object Detection with Unsupervised Pre-Training
PY - 2024
ER -
Less is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentation Core A* Conference‡ Citation: 46#
Proceedings of the 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023
Li Li, Hubert P. H. Shum and Toby P. Breckon
Topics: Environment Sensing
Webpage Cite This Plain Text
Proceedings of the 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023
Li Li, Hubert P. H. Shum and Toby P. Breckon
Topics: Environment Sensing
Webpage Cite This Plain Text
Li Li, Hubert P. H. Shum and Toby P. Breckon, "Less is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentation," in CVPR '23: Proceedings of the 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 9361-9371, Vancouver, Canada, IEEE/CVF, Jun 2023.
Bibtex @inproceedings{li23less,
author={Li, Li and Shum, Hubert P. H. and Breckon, Toby P.},
booktitle={Proceedings of the 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition},
series={CVPR '23},
title={Less is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentation},
year={2023},
month={6},
pages={9361--9371},
numpages={11},
doi={10.1109/CVPR52729.2023.00903},
publisher={IEEE/CVF},
location={Vancouver, Canada},
}
RIS author={Li, Li and Shum, Hubert P. H. and Breckon, Toby P.},
booktitle={Proceedings of the 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition},
series={CVPR '23},
title={Less is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentation},
year={2023},
month={6},
pages={9361--9371},
numpages={11},
doi={10.1109/CVPR52729.2023.00903},
publisher={IEEE/CVF},
location={Vancouver, Canada},
}
TY - CONF
AU - Li, Li
AU - Shum, Hubert P. H.
AU - Breckon, Toby P.
T2 - Proceedings of the 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition
TI - Less is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentation
PY - 2023
Y1 - 6 2023
SP - 9361
EP - 9371
DO - 10.1109/CVPR52729.2023.00903
PB - IEEE/CVF
ER -
Paper Supplementary Material GitHub YouTubeAU - Li, Li
AU - Shum, Hubert P. H.
AU - Breckon, Toby P.
T2 - Proceedings of the 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition
TI - Less is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentation
PY - 2023
Y1 - 6 2023
SP - 9361
EP - 9371
DO - 10.1109/CVPR52729.2023.00903
PB - IEEE/CVF
ER -
DurLAR: A High-fidelity 128-Channel LiDAR Dataset with Panoramic Ambientand Reflectivity Imagery for Multi-Modal Autonomous Driving Applications H5-Index: 51# Citation: 20#
Proceedings of the 2021 International Conference on 3D Vision (3DV), 2021
Li Li, Khalid N. Ismail, Hubert P. H. Shum and Toby P. Breckon
Topics: Robotics, 3D Reconstruction, Environment Sensing, Datasets
Webpage Cite This Plain Text
Proceedings of the 2021 International Conference on 3D Vision (3DV), 2021
Li Li, Khalid N. Ismail, Hubert P. H. Shum and Toby P. Breckon
Topics: Robotics, 3D Reconstruction, Environment Sensing, Datasets
Webpage Cite This Plain Text
Li Li, Khalid N. Ismail, Hubert P. H. Shum and Toby P. Breckon, "DurLAR: A High-fidelity 128-Channel LiDAR Dataset with Panoramic Ambientand Reflectivity Imagery for Multi-Modal Autonomous Driving Applications," in 3DV '21: Proceedings of the 2021 International Conference on 3D Vision, pp. 1227-1237, IEEE, Dec 2021.
Bibtex @inproceedings{li21durlar,
author={Li, Li and Ismail, Khalid N. and Shum, Hubert P. H. and Breckon, Toby P.},
booktitle={Proceedings of the 2021 International Conference on 3D Vision},
series={3DV '21},
title={DurLAR: A High-fidelity 128-Channel LiDAR Dataset with Panoramic Ambientand Reflectivity Imagery for Multi-Modal Autonomous Driving Applications},
year={2021},
month={12},
pages={1227--1237},
numpages={11},
doi={10.1109/3DV53792.2021.00130},
publisher={IEEE},
}
RIS author={Li, Li and Ismail, Khalid N. and Shum, Hubert P. H. and Breckon, Toby P.},
booktitle={Proceedings of the 2021 International Conference on 3D Vision},
series={3DV '21},
title={DurLAR: A High-fidelity 128-Channel LiDAR Dataset with Panoramic Ambientand Reflectivity Imagery for Multi-Modal Autonomous Driving Applications},
year={2021},
month={12},
pages={1227--1237},
numpages={11},
doi={10.1109/3DV53792.2021.00130},
publisher={IEEE},
}
TY - CONF
AU - Li, Li
AU - Ismail, Khalid N.
AU - Shum, Hubert P. H.
AU - Breckon, Toby P.
T2 - Proceedings of the 2021 International Conference on 3D Vision
TI - DurLAR: A High-fidelity 128-Channel LiDAR Dataset with Panoramic Ambientand Reflectivity Imagery for Multi-Modal Autonomous Driving Applications
PY - 2021
Y1 - 12 2021
SP - 1227
EP - 1237
DO - 10.1109/3DV53792.2021.00130
PB - IEEE
ER -
Paper Dataset GitHub YouTubeAU - Li, Li
AU - Ismail, Khalid N.
AU - Shum, Hubert P. H.
AU - Breckon, Toby P.
T2 - Proceedings of the 2021 International Conference on 3D Vision
TI - DurLAR: A High-fidelity 128-Channel LiDAR Dataset with Panoramic Ambientand Reflectivity Imagery for Multi-Modal Autonomous Driving Applications
PY - 2021
Y1 - 12 2021
SP - 1227
EP - 1237
DO - 10.1109/3DV53792.2021.00130
PB - IEEE
ER -
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