Yufan Zhou
Research Scientist at Adobe Research
Email: yufanzho AT buffalo DOT eduBio
Currently my research focuses on generative models. More specifically, I'm interested in:
- Multi-modal generative models (assistants) which are more user-friendly;
- Customizing pre-trained generative models;
- Saving the training or dataset construction cost in generative modeling;
I obtained my Ph.D. from the Department of Computer Science and Engineering, University at Buffalo, under the supervision of
Prof. Jinhui Xu and
Prof. Changyou Chen.
I received my B.E. degree from Zhejiang University.
I worked as a Research Intern with Chunyuan Li (Microsoft), Ruiyi Zhang (Adobe), Bingchen Liu (ByteDance).
Self-motivated students who are interested in interning at Adobe, or seeking research collaborations, feel free to reach out to me.
News
- One paper accepted by CoLM 2024.
- One paper accepted by ACL 2024.
- Two papers accepted by CVPR 2024.
- One paper accepted by ICLR 2024.
Selected Papers [More]
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Efficient method to construct dataset for subject-driven T2I generation, which can save at least tens of thousands of GPU hours.
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IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024.An assistant which can generate creative images for specific user-input subject along with text explanation and elaboration in 2-5 seconds, without any fine-tuning.
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A novel framework for customized text-to-image generation without the use of regularization.
We can efficiently customize a large-scale text-to-image generation model on single GPU, with only one image provided by the user. -
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023.We propose a method termed Corgi, which can better generate image embeddings from text inside multimodal embedding space.
It benefits both standard and language-free text-to-image generation. And yes, I do have a Corgi. -
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022.Our proposed work, Lafite, is the first work which can successfully train text-to-image generation model with image-only dataset.
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AAAI conference on Artificial Intelligence (AAAI), 2022.
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International Conference on Learning Representations (ICLR), 2021.
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Conference on Neural Information Processing Systems (NeurIPS), 2020.
Professional Service
- Conferences Program Committee/Reviewer: NeurIPS 2020, 2021, 2022, 2023; ICML 2021, 2022, 2023, 2024; ICLR 2022, 2023, 2024; CVPR 2023, 2024; AISTATS 2021; AAAI 2021, 2022; IJCAI 2021; EMNLP 2022, 2023; ECCV 2024; ACL 2023;
- Journal Reviewer: IEEE Transactions on Neural Networks and learning systems; IEEE Transactions on Circuits and Systems for Video Technology;