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Junlin (Hans) Han |
Profile
Greetings, welcome to my website!- I am a researcher at GenAI, Meta, and a second-year PhD (DPhil) student at the Torr Vision Group, University of Oxford, working with Prof. Philip Torr. Before that, I worked as a research scientist at Cybever, a 3D AIGC startup for a few months. I obtained my BSc from the Australian National University under the supervision of Dr. Lars Petersson, Prof. Hongdong Li, and Prof. Ian Reid.
- I acknowledge that information asymmetry can significantly hinder research opportunities for junior students. If you’re interested in chatting about life, research, or potential collaborations, feel free to email me.
News
- [03.2025] One paper on point-cloud segmentation was accepted to CVPR 2025, congrats to Zhaochong!
- [12.2024] Our previous work on low-level vision won the best paper award in Remote Sensing!
- [12.2024] We will be organizing the 2nd Workshop on Foundation Models in the Wild at ICLR 2025!
- [11.2024] Two papers (3D-GPT and DreamBeast) were accepted to 3DV 2025. Congratulations to Chunyi and Runjia! 3D-GPT is pioneering work in large-scale 3D scene generation, and DreamBeast is a fascinating project generating fantastical 3D animals.
- [07.2024] VFusion3D and Unicorns were accepted to ECCV 2024! VFusion3D is the first work exploring scalable 3D generative/reconstruction models as a step towards a 3D foundation. Check it out if you are interested in 3D generation.
- [04.2024] We are organizing ICML 2024 Foundation Models in the Wild Workshop, submissions on related topics are very welcomed!
- [10.2023] Starting my PhD at Meta and Oxford!
- [07.2023] Hyperbolic Audio-visual Zero-shot Learning was accepted to ICCV 2023!
- [07.2023] Graduated from ANU with First-Class Honours.
- [10.2022] Awarded as a top reviewer in NeurIPS 2022!
- [07.2022] Blind Image Decomposition (BID) was accepted to ECCV 2022! A new low-level vision task that better adapts to complex real-world scenarios. Check our project page for more.
- [05.2022] You Only Cut Once (YOCO) was accepted to ICML 2022! Check here for our work on how to perform data augmentation.
- [12.2021] Joined Australian Institute for Machine Learning (AIML), University of Adelaide as a visiting research intern, hosted by Prof. Ian Reid!
Research Interests
- Recognizing that data is the core source from which AI's capabilities emerge, I study how data can be effectively created, utilized, and understood to enhance the capabilities of AI systems.
- My work spans the entire data lifecycle, from the initial creation and manipulation of visual data to the development of methodologies that strategically leverage diverse data sources for improved model training and performance. Moreover, I investigate the fundamental principles that govern the interaction between data and AI, striving to understand how data shapes intelligence and decision-making. Through this multifaceted exploration of data, my research aims to pave the way for more powerful, efficient, reliable, and ultimately, more human-aligned AI. You can click on to expand detailed projects:
(1) Generation and manipulation of 2D, 3D, and 4D visual data,
Selected projects: Image decomposition, LLM for 3D scene generation, High-quality 3D asset generation
(2) Use augmented, synthetic, and distilled data for training AI models,
Selected projects: How to perform data augmentation, Synthetic data for training 3D generative models
I am also interested in extending my research to other scientific domains, such as exploring the applications of AI in the field of health and biology.
Education
Postgraduate (01.2024 - ongoing)- PhD in Computer Vision, University of Oxford Supervised by Prof. Philip Torr
- B.S. Information Technology (Honours), ANU Supervised by Dr. Lars Petersson, Prof. Hongdong Li, and Prof. Ian Reid.
Research Experience
PhD Student Researcher at GenAI, Meta (10.2023 - ongoing)- Topics: 3D&4D generation, Multimodal Large Language Models
- Hosted by Dr. Filippos Kokkinos
- Topics: 3D generation
- Topics: Data-centric AI, Memorability
- Advised by Prof. Ian Reid
- Topics: Generative models, Self-supervised learning
- Advised by Dr. Lars Petersson, Prof. Hongdong Li
Publications
Representative papers (as leading author) are highlighted.Academic Services
- Workshop Organization 2nd Workshop on Foundation Models in the Wild at ICLR 2025
- Conference review CVPR 2022 2023 2024 2025, ICCV 2023, ECCV 2022 2024, ICML 2022 2024 2025, NeurIPS 2022 2023, ICLR 2023 2024 2025, SIGGRAPH Asia 2024, ACCV 2022, BMVC 2023, WACV 2024, AAAI 2023
- Journal review Transactions on Pattern Analysis and Machine Intelligence (TPAMI), International Journal of Computer Vision (IJCV), Transactions on Image Processing (TIP), Transactions on Geoscience and Remote Sensing (TGRS)
Foundation Models in the Wild at ICML 2024
Skills
- Programming Language Proficient in MATLAB, Python
- Tool NumPy, PyTorch, Git, LaTeX
- Language English, Singlish, and Madarian
Familiar with Java, Haskell, R, CSS, Html, Assembly (ARMV7), SQL
Awards
- Meta PhD Scholarship, 2023 for PhD research at University of Oxford
- Best paper award, 2022 from Remote Sensing journal
- Chancellor's Letter of Commendation, 2022 for best academic performance at Australian National University
- Top Reviewer, 2022 NeurIPS (Conference on Neural Information Processing Systems)
- Second Best Presentation Award, 2021 AIM (Active Integrated Matter) Conference
- Top-up Scholarship, 2021 for research work at Data61-CSIRO
- Undergraduate Vacation Scholarship, 2020 for summer research at Data61-CSIRO
Miscs
- At the beginning, I was born and raised in Chengdu, which is famous for spice and pandas.
- I studied and lived in China, Singapore, Australia, and UK.
- Aside from research, I am passionate about traveling (especially nature travel), cooking, gaming, and swimming.