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I am a First-year Ph.D. student at Tsinghua University, advised by Prof. Jie Zhou and Prof. Jiwen Lu . In 2024, I received my B.S. degree in the Department of Automation, Tsinghua University. I am broadly interested in computer vision and deep learning. My current research focuses on visual generation. |
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(*Equal Contribution, #Corresponding Author) |
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Yixuan Zhu, Haolin Wang, Shilin Ma, Wenliang Zhao, Yansong Tang, Lei Chen#, Jie Zhou IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025 [Coming soon] We introduce FADE—a training-free yet highly effective video editing approach that fully leverages the inherent priors from pre-trained video diffusion models via frequency-aware factorization. |
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Yixuan Zhu*, Haolin Wang*, Ao Li, Wenliang Zhao, Yansong Tang, Jingxuan Niu, Lei Chen#, Jie Zhou, Jiwen Lu The Thirteenth International Conference on Learning Representations (ICLR), 2025 [Coming soon] We propose InstaRevive, a straightforward yet powerful image enhancement framework that employs score-based diffusion distillation to harness potent generative capability and minimize the sampling steps. |
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Wenliang Zhao, Haolin Wang, Jie Zhou, Jiwen Lu European Conference on Computer Vision (ECCV), 2024 [arXiv] [Code] DC-Solver is designed to improve alignment in predictor-corrector diffusion samplers (while also applicable to predictor-only samplers). With negligible search costs, DC-Solver can achieve as few as 5 sampling steps (NFE). |
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