Sydney AI Meetup 2025
Monthly Events
This AI meetup is designed to enhance collaboration and networking among HDR students, academic staff, and industry professionals. It offers a unique platform for participants to engage in meaningful discussions, foster partnerships, and explore opportunities for external collaboration, joint research projects, and industry internships. By facilitating these interactions, the event aims to drive innovation and promote knowledge exchange within the AI research community.
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| Title | 3D Generative AI Compression with Context Models |
| Speaker | Prof. Jianfei Cai, Monash University |
| Date | Feb 14, 2025 |
| Time | 01:00 PM Canberra, Melbourne, Sydney |
| Register | Link |
| Join the LinkedIn Group Sydney AI Meetup Community for the latest event update, discussion, and networking. | |
| Delivery | In person & Online |
| Location | Lecture Theatre 123, Level 1 School of Computer Science (J12) 1 Cleveland St, Darlington NSW 2008 |
| Streaming | https://uni-sydney.zoom.us/j/87234136394 |
| Catering | Free light lunch, 12:30 pm to 1:00 pm |
| Intro | While 3D vision is not a new field, it has recently undergone a transformation driven by significant advancements in generative models. 3D Generative AI or Spatial AI has emerged as a major focus within the 3D vision community. At its core, the field has experienced a paradigm shift with the introduction of Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS), which have redefined 3D representation. Leveraging deep learning techniques and 2D image supervision, these methods have achieved remarkable results in view synthesis. However, their reliance on extensive feature sets and large network parameters poses significant storage challenges. To address this, we have developed a series of innovative approaches—CNC, HAC, and FCGS—focused on efficient and effective compression of these advanced 3D representations. Central to our work is the use of context models, which play a pivotal role in optimizing 3D compression while preserving visual quality. This talk will delve into the design principles and impact of these techniques, paving the way for more efficient 3D vision applications. |
Jianfei Cai is a Professor at Faculty of IT, Monash University, where he had served as the inaugural Head for the Data Science & AI Department. Before that, he was Head of Visual and Interactive Computing Division and Head of Computer Communications Division in Nanyang Technological University (NTU). His major research interests include computer vision, deep learning and multimedia. He has successfully trained 40+ PhD students with three getting NTU SCSE Outstanding PhD thesis award and one getting Monash FIT Graduate Research Student Excellence Award. Many of his PhD students joined leading IT companies such as Meta, Apple, Amazon, Adobe and TikTok or become faculty members in reputable universities. He is a co-recipient of paper awards in ACCV, ICCM, IEEE ICIP and MMSP, and a winner of Monash FIT’s Dean's Researcher of the Year Award. He serves or has served as an Associate Editor for TPAMI, IJCV, IEEE T-IP, T-MM, and T-CSVT as well as serving as Area Chair for CVPR, ICCV, ECCV, IJCAI, ACM Multimedia, ICME, ICIP and ISCAS. He was the Chair of IEEE CAS VSPC-TC during 2016-2018. He had served as the leading TPC Chair for IEEE ICME 2012 and the best paper award committee chair & co-chair for IEEE T-MM 2020 & 2019. He is the leading General Chair for ACM Multimedia 2024, and a Fellow of IEEE.
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Silver Sponsor
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Bronze Sponsors
Sponsors
Chiarman: Lei Wang (UoW)
Treasurer: Qiang Wu (UTS)
Publicity Chair: Yuankai Qi (MQ)
Industry Chair: Susan Zhang (UoW)
Seminar Chair: Dong Gong (UNSW),
Chang Xu (USyd)
Committee member:
Ling Chen (UTS),
Yi Guo (WSU),
Markus Hagenbuchner (UoW),
Son Lam Phung (UoW),
Zhenghao Chen (UoN),
Rosalind Wang (WSU),
Yanjun Zhang (UTS),
For enquiries, please contact the organizing committee via sydneyaimeetup@mq.edu.au
