Tang, M. Q., Abdelzad, V., Huang, C., Sedwards, S., & Czarnecki, K. (2024). 3D Object Detection with Track-Based Auto-Labelling Using Very Sparsely Labelled Data Presented at the International Conference on Intelligent Transportation Systems (ITSC) conference. Edmonton, AB, Canada: IEEE. https://doi.org/10.1109/ITSC58415.2024.10919741 (Original work published 2024)
Reference author: Sean Sedwards
First name
Sean
Last name
Sedwards
Chow, A., Riddell, E., Wang, Y., Sedwards, S., & Czarnecki, K. (2025). OV-SCAN: Semantically Consistent Alignment for Novel Object Discovery in Open-Vocabulary 3D Object Detection Presented at the IEEE/CVF/International/Conference/on/Computer/Vision/(ICCV) conference. Honolulu, USA: Computer Vision Foundation. Retrieved from https://openaccess.thecvf.com/content/ICCV2025/html/Chow_OV-SCAN_Semantically_Consistent_Alignment_for_Novel_Object_Discovery_in_Open-Vocabulary_ICCV_2025_paper.html (Original work published 2025)
Wang, Y., Azadani, M. N., Sedwards, S., & Czarnecki, K. (2025). Leo-mini: An efficient multimodal large language model using conditional token reduction and mixture of multi-modal experts Presented at the Conference on Empirical Methods in Natural Language Processing (EMNLP) conference. Suzhou, China. https://doi.org/10.18653/v1/2025.emnlp-main.368 (Original work published 2025)
Wang, Y., Riddell, E., Chow, A., Sedwards, S., & Czarnecki, K. (2026). Mitigating the modality gap: Few-shot out-of-distribution detection with multi-modal prototypes and image bias estimation Presented at the IEEE/CVF/Winter/Conference/on/Applications/of/Computer/Vision conference. Tucson, Arizona, USA. Retrieved from https://openreview.net/pdf?id=tgnTVmRybs
Azadani, M. N., Riddell, J., Sedwards, S., & Czarnecki, K. (2026). Rethinking the Mixture of Vision Encoders Paradigm for Enhanced Visual Understanding in Multimodal LLMs Transactions on Machine Learning Research. Retrieved from https://openreview.net/pdf?id=tgnTVmRybs (Original work published 2026)
Wang, Y., Azadani, M. N., Sedwards, S., & Czarnecki, K. (2025). Hawaii: Hierarchical Visual Knowledge Transfer for Efficient Vision-Language Models Presented at the Advances in Neural Information Processing Systems (NeurIPS) conference. San Diego, USA: Curran Associates, Inc. Retrieved from https://proceedings.neurips.cc/paper_files/paper/2025/file/018af723a54a6d3bc5706d3a3126abf0-Paper-Conference.pdf (Original work published 2025)
Tang, M. Q., Sedwards, S., Huang, C., & Czarnecki, K. (2025). How Hard is Snow? A Paired Domain Adaptation Dataset for Clear and Snowy Weather: CADC+ Presented at the IEEE Intelligent Vehicles Symposium (IV) conference. Cluj, Romania: IEEE. https://doi.org/10.1109/IV64158.2025.11097651 (Original work published 2025)
Huang, C., Abdelzad, V., Sedwards, S., & Czarnecki, K. (2025). VADet: Multi-Frame LiDAR 3D Object Detection Using Variable Aggregation Presented at the 2025 IEEE CVF Winter Conference on Applications of Computer Vision (WACV) conference. Tucson, AZ, USA: IEEE. https://doi.org/10.1109/WACV61041.2025.00079 (Original work published 2025)
Huang, C., Abdelzad, V., Sedwards, S., & Czarnecki, K. (2024). SOAP: Cross-sensor Domain Adaptation for 3D Object Detection Using Stationary Object Aggregation Pseudo-labelling Presented at the 2024 IEEE CVF Winter Conference on Applications of Computer Vision (WACV) conference. Waikoloa, HI, USA: IEEE. https://doi.org/10.1109/WACV57701.2024.00332 (Original work published 2024)
Kido, K., Sedwards, S., & Hasuo, I. (2018). Bounding Errors Due to Switching Delays in Incrementally Stable Switched Systems Oxford, United Kingdom: Elsevier. Retrieved from https://www.sciencedirect.com/science/article/pii/S2405896318311583