Jie An

Jie An | 安捷

Jie An is a Ph.D. student (2020 - now) in Computer Science at University of Rochester, advised by Prof. Jiebo Luo. Prior to that, he obtained the B.S. (2012 - 2016) and M.S. (2016 - 2019) in Applied Mathematics from Peking University, advised by Prof. Jinwen Ma. Jie has been a research intern at Apple, Microsoft Cloud & AI, Meta FAIR, Tencent AI Lab, Baidu Big Data Lab, and Face++.

Research

Jie's research focuses on improving the performance and extending the capability of GenAI models. He is particularly interested in image style transfer, generative model, image/video generation, and multi-modal generation/evaluation.

I am actively seeking opportunities for a full-time Research Scientist position. Please feel free to reach out if you see a good fit.

Email / CV / Google Scholar / Github / LinkedIn / Name Pronounce

News

[2024/06] Our work OpenLEAF: Open-Domain Interleaved Image-Text Generation and Evaluation is accepted to ACM MM 2024 BNI track. Many thanks to the collaborators!
[2024/05] Our work Bring Metric Functions into Diffusion Models is accepted to IJCAI 2024. Many thanks to the collaborators!
[2024/03] We will organize the first workshop on Visual-Language Alignment in Text-Guided Multi-Modal Generation (T2MM) in conjunction with #ICME2024. Welcome to submit your workshop papers!
[2024/03] I will join Apple as a research intern this summer.
[2023/02] I will join Microsoft Cloud & AI as a research intern.

Publications

	OpenLEAF: Open-Domain Interleaved Image-Text Generation and Evaluation Jie An^, Zhengyuan Yang, Linjie Li, Jianfeng Wang, Kevin Lin, Zicheng Liu, Lijuan Wang, Jiebo Luo ACM MM (BNI Track)* 2024 \| BibTex We introduce a benchmark dataset, an evaluation pipeline, and a set of baseline models for interleaved image-text generation task.
	Bring Metric Functions into Diffusion Models Jie An, Zhengyuan Yang, Jianfeng Wang, Linjie Li, Zicheng Liu, Lijuan Wang, Jiebo Luo IJCAI 2024 \| BibTex We study how to ultilize LPIPS loss in diffusion model training to improve the image generation quality.
	Latent-Shift: Latent Diffusion with Temporal Shift for Efficient Text-to-Video Generation Jie An^, Songyang Zhang^, Harry Yang, Sonal Gupta, Jia-Bin Huang, Jiebo Luo and Xi Yin Arxiv 2023 \| Project Page \| BibTex We propose an efficient text-to-video generation method based on latent diffusion model and temporal shift.
	Learning to Evaluate the Artness of AI-generated Images Junyu Chen, Jie An, Hanjia Lyu, Jiebo Luo TMM 2024 \| BibTex We propose a rank-based method to evaluate the artness level of AI-generated artworks.
	Holistic Visual-Textual Sentiment Analysis with Prior Models Junyu Chen, Jie An, Hanjia Lyu and Jiebo Luo MIPR 2024 \| BibTex We ultilize multi-modal expert features to assist the sentiment analysis task.
	QuantArt: Quantizing Image Style Transfer Towards High Visual Fidelity Siyu Huang^, Jie An^, Donglai Wei, Jiebo Luo and Hanspeter Pfister CVPR 2023 \| Code \| BibTex QuantArt allows the style transfer model take the reference from the whole artistic picture dataset, leading to improved visual fidelity.
	Make-A-Video: Text-to-video Generation Without Text-video Data. Uriel Singer^, Adam Polyak^, Thomas Hayes^, Xi Yin^, Jie An, Songyang Zhang, Qiyuan Hu, Harry Yang, Oron Ashual, Oran Gafni, Devi Parikh, Sonal Gupta and Yaniv Taigman ICLR 2023 \| BibTex We propose a text-to-video generation method based on diffusion model.
	Domain-Scalable Unpaired Image Translation via Latent Space Anchoring Siyu Huang^, Jie An^ , Donglai Wei, Zudi Lin, Jiebo Luo and Hanspeter Pfister TPAMI \| Code \| BibTex We propose a GAN-based multi-domain image translation method that can extend to any unseen domain without the need to train the core backbone.
	Is Bigger Always Better? An Empirical Study on Efficient Architectures for Style Transfer and Beyond Jie An, Tao Li, Haozhi Huang, Jinwen Ma and Jiebo Luo WACV 2023 \| BibTex We study whether the big VGG19 architecture is the best backbone for image style transfer and explore its efficient alternatives.
	Facial Attribute Transformers for Precise and Robust Makeup Transfer Zhaoyi Wan, Haoran Chen, Jie An, Wentao Jiang, Cong Yao and Jiebo Luo WACV 2022 \| BibTex We propose an new transformer-based method for makeup transfer and removal.
	ArtFlow: Unbiased Image Style Transfer via Reversible Neural Flows Jie An^, Siyu Huang^, Yibing Song, Dejing Dou, Wei Liu and Jiebo Luo CVPR 2021 \| Code \| BibTex We propose an unbiased style transfer method based on neural flows to address the content leak issue in style transfer.
	Global Image Sentiment Transfer Jie An, Tianlang Chen, Songyang Zhang and Jiebo Luo ICPR 2020 \| BibTex We propose a method to transfer the global sentiment of images.
	Ultrafast photorealistic style transfer via neural architecture search Jie An^, Haoyi Xiong^, kun Huan and Jiebo Luo AAAI 2020 (Oral Presentation) \| Code \| BibTex We propose a neural architecture search framework to discover efficient architectures for photo-realistic style transfer.
	Pyramid attention network for semantic segmentation Hanchao Li, Pengfei Xiong, Jie An, and Lingxue Wang BMVC 2018 \| BibTex We propose a new network architecture for semantic image segmentation.

Internship

	Apple [2024/05 - Present] Advisor: Alexander Schwing, Andy (De) Wang, Pengsheng Guo
	Microsoft Cloud & AI [2023/02 - 2024/4] Advisor: Zhengyuan Yang, Jianfeng Wang, Linjie Li, Lijuan Wang, Zicheng Liu Project: Diffusion model and visual-language generation.
	Meta FAIR [2022/05 - 2022/12] Advisor: Harry Yang, Xi Yin, Sonal Gupta Project: Text-to-video generation.
	Tencent AI Lab [2019/07 - 2021/07] Advisor: Yibing Song, Haozhi Huang Project: Image artistic style transfer.
	Baidu Big Data Lab [2019/01 - 2019/07] Advisor: Haoyi Xiong, Jun (Luke) Huan Project: Image artistic style transfer.
	Megvii (Face++) [2017/10 - 2018/06] Advisor: Pengfei Xiong Project: Semantic Segmentation.

Services

Conference Reviewer

CVPR 2022 - 2024
ICCV 2021, 2023
ECCV 2022
WACV 2022 - 2024
NeurIPS 2024
EMNLP 2023
ACL 2023
ICME 2023
ACM MM 2023
ACM MM Asia 2021
ICASSP 2023

Conference Program Committee Member

AAAI 2023 - 2024

Journal Reviewer

TPAMI, TMM, TNNLS, APSIPA

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