Open Access
| Issue |
ITM Web Conf.
Volume 84, 2026
2026 International Conference on Advent Trends in Computational Intelligence and Data Science (ATCIDS 2026)
|
|
|---|---|---|
| Article Number | 04024 | |
| Number of page(s) | 5 | |
| Section | Computer Vision, Robotic Systems, and Intelligent Control | |
| DOI | https://doi.org/10.1051/itmconf/20268404024 | |
| Published online | 06 April 2026 | |
- Z. He, W. Ran, S. Liu, et al. Low-light Image Enhancement with Multi-scale Attention and Frequency-domain Optimization. IEEE Transactions on Circuits and Systems for Video Technology, 34(4): 2861–2875. (2024) [Google Scholar]
- C. R. Qi, H. Su, K. Mo, et al. PointNet++: Deep hierarchical feature learning on point sets in a metric space// Proceedings of the 31st International Conference on Neural Information Processing Systems (NeurIPS), 5099–5108. (2017) [Google Scholar]
- Z. Li et al., BEVFormer: Learning Bird’s-Eye-View Representation From LiDAR-Camera via Spatiotemporal Transformers, in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 47, no. 3, pp. 2020–2036, doi: 10.1109/TPAMI.2024.351545. (2025) [Google Scholar]
- Y. Pang, J. Zhang, and Y. Ning Research Progress on LiDAR and Camera Fusion Target Detection Technology in Autonomous Driving. Automobile technology, 1-14 (2026) https://doi.org/10.19620/j.cnki.1000-3703.20250225. [Google Scholar]
- W. Ji, Y. Li, and J. Wang, et al. A Review of 3D Object Detection Based on the Fusion of Lidar and Camera. Computer Science,1-24. (2026) https://link.cnki.net/urlid/50.1075.tp.20250717.1650.024. [Google Scholar]
- S. Vora, A. H. Lang, B. Helou, et al. PointPainting: Sequential Fusion for 3D Object Detection// Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). Seattle, WA, USA: IEEE, 4604-4612. (2020) [Google Scholar]
- J. Philion, S. Fidler. Lift, Splat, Shoot: Encoding Images from Arbitrary Camera Rigs by Implicitly Unprojecting to 3D// Proceedings of the European Conference on Computer Vision (ECCV). Glasgow, UK: Springer, 194-210. (2020) [Google Scholar]
- Z. Liu, H. Tang, A. Amini, et al. BEVFusion: Multi-task multi-sensor fusion with unified bird’s-eye view representation//2023 IEEE International Conference on Robotics and Automation. IEEE, 2774-2781. (2023) [Google Scholar]
- T. T. Liang, H. W. Xie, K. C. Yu, et al. BEVFusion: A Simple and Robust LiDAR-Camera Fusion Framework// Proceedings of the 36th Conference on Neural Information Processing Systems (NIPS). New Orleans, LA, USA: NIPS, (2022) [Google Scholar]
- X. Bai, Z. Hu, X. Zhu, et al. TransFusion: Robust LiDAR-camera fusion for 3D object detection with transformers//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1090-1099. (2022) [Google Scholar]
- S. Pang, D. Morris, H. Radha. CLOCs: Camera-LiDAR object candidates fusion for 3D object detection//2020 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE, 10386-10393. (2020) [Google Scholar]
- V. Vats, M. B. Nizam, J. Davis. VaLID: Verification as Late Integration of Detections for LiDAR-Camera Fusion. https://arxiv.org/abs/2409.15529. (2025) [Google Scholar]
- H. Dong, W. H. Gu, X. J. Zhang, et al. SuperFusion: Multilevel LiDAR-Camera Fusion for Long-Range HD Map Generation// Proceedings of the 2024 IEEE International Conference on Robotics and Automation (ICRA). Yokohama, Japan: IEEE, 9056-9062. (2024) [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.