Jiwen Yu

I will be enrolling the Department of Electrical and Electronic Engineering at the University of Hong Kong as a PhD student in 2024 fall, supervised by Prof. Xihui Liu at HKU-MMLab. I will be working on research topics related to Computer Vision and Embodied AI. Prior to this, I obtained my master's degree from Peking University, where I was advised by Prof. Jian Zhang.

Email / Google Scholar / Github / CV

Selected Publications

	AnimateZero: Video Diffusion Models are Zero-Shot Image Animators Jiwen Yu, Xiaodong Cun, Chenyang Qi, Yong Zhang, Xintao Wang, Ying Shan, Jian Zhang ArXiv, 2023 code / arXiv / paper / project page We propose AnimateZero, a zero-shot approach for image animation on generated images. AnimateZero also supports various applications, such as video editing, frame interpolation, real image animation, and more.
	CRoSS: Diffusion Model Makes Controllable, Robust and Secure Image Steganography Jiwen Yu, Xuanyu Zhang, Youmin Xu, Jian Zhang NeurIPS, 2023 code / arXiv We propose a novel diffusion-based image steganography framework named Controllable, Robust, and Secure Image Steganography (CRoSS). This framework offers significant advantages in controllability, robustness, and security compared to cover-based image steganography methods. Importantly, these benefits are achieved without requiring additional training.
	FreeDoM: Training-Free Energy-Guided Conditional Diffusion Model Jiwen Yu, Yinhuai Wang, Chen Zhao, Bernard Ghanem, Jian Zhang ICCV, 2023 code / arXiv FreeDoM is a simple but effective training-free method generating results under control from various conditions using unconditional diffusion models.
	Zero-Shot Image Restoration Using Denoising Diffusion Null-Space Model Yinhuai Wang, Jiwen Yu, Jian Zhang (denotes equal contribution) ICLR, 2023 (Oral Presentation)* project page / arXiv / code We bring Range-Null space Decomposition (RND) into diffusion models, enabling diverse image restoration tasks in a zero-shot manner, without extra training or optimization.

Experience
	Research Intern, Tencent AI Lab April, 2023 - January, 2024

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