Tianhe Wu

Ph.D. Student
City University of Hong Kong

E-mail: tianhewu-c@my.cityu.edu.hk

About Me

Hi, I'm Tianhe Wu, a Ph.D. student at the City University of Hong Kong (CityU), where I am supervised by Prof. Kede Ma. My current research focuses on Generative AI (GenAI), with a particular interest in post-training techniques for LLMs and VLMs.

Before joining CityU, I completed my M.Sc. degree (2022-2025) at Tsinghua University, under the supervision of Prof. Yujiu Yang. I received my B.Eng. degree (2018-2022) from the Beijing University of Technology.

Education

	City University of Hong Kong Ph.D. Student in Department of Computer Science Supervisor: Prof. Kede Ma	Sep. 2025 - Present
	Tsinghua University Master Degree in Big Data Technology and Engineering Supervisor: Prof. Yujiu Yang	Sep. 2022 - Jun. 2025
	Beijing University of Technology Bachelor Degree in Computer Science	Sep. 2018 - Jun. 2022

News

2025-09: Paper VisualQuality-R1 obtained NeurIPS 2025 Spotlight, jointly with OPPO and CityU.
2025-02: One paper was accepted at CVPR 2025, jointly with OPPO and CityU.
2024-07: One paper was accepted at ECCV 2024, jointly with Tsinghua and CityU.
2023-09: A paper was accepted to NeurIPS 2023 during my time at Tsinghua University.
2022-06: I published my first conference paper, MANIQA, during my time at Tsinghua University.
2022-04: Our team at Tsinghua won the NTIRE 2022 Perceptual Image Quality Assessment Challenge, taking first place in both Track 1 (Full-Reference) and Track 2 (No-Reference).

Selected Publications
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	NeurIPS 2025 DP2O-SR: Direct Perceptual Preference Optimization for Real-World Image Super-Resolution Rongyuan Wu, Lingchen Sun, Zhengqiang Zhang, Shihao Wang, Tianhe Wu, Qiaosi Yi, Shuai Li, Lei Zhang NeurIPS, 2025 arXiv / Code Direct perceptual preference optimization for image super-resolution.
	Preprint 2025 The Unanticipated Asymmetry Between Perceptual Optimization and Assessment Jiabei Zhang, Qi Wang, Siyu Wu, Du Chen, Tianhe Wu^† arXiv, 2025 arXiv / Code Our comprehensive study highlights the asymmetries between assessment and optimization.
	NeurIPS 2025 VisualQuality-R1: Reasoning-Induced Image Quality Assessment via Reinforcement Learning to Rank Tianhe Wu, Jian Zou, Jie Liang, Lei Zhang, Kede Ma NeurIPS (Spotlight), 2025 arXiv / Code A reasoning-enabled visual quality model capable of delivering both qualitative descriptions and quantitative ratings.
	CVPR 2025 Toward Generalized Image Quality Assessment: Relaxing the Perfect Reference Quality Assumption Du Chen, Tianhe Wu, Kede Ma, Lei Zhang CVPR, 2025 arXiv / Project Page / Code / Dataset / Benchmark A generalized FR-IQA model for low-level vision, applicable to both perfect and imperfect reference scenarios.
	ECCV 2024 A Comprehensive Study of Multimodal Large Language Models for Image Quality Assessment Tianhe Wu, Kede Ma, Jie Liang, Yujiu Yang, Lei Zhang ECCV, 2024 arXiv / Code A systematic study on the ability of multimodal large language models to perceive and assess image quality.
	NeurIPS 2023 Assessor360: Multi-sequence Network for Blind Omnidirectional Image Quality Assessment Tianhe Wu, Shuwei Shi, Haoming Cai, Mingdeng Cao, Jing Xiao, Yinqiang Zheng, Yujiu Yang NeurIPS, 2023 arXiv / Code We present a new framework for blind omnidirectional IQA.
	CVPR Workshop 2022 Attentions Help CNNs See Better: Attention-based Hybrid Image Quality Assessment Network Shanshan Lao, Yuan Gong, Shuwei Shi, Sidi Yang, Tianhe Wu, Jiahao Wang, Weihao Xia, Yujiu Yang CVPR Workshop (Oral Presentation), 2022 arXiv / Code The champion method for NTIRE2022 FR IQA.
	CVPR Workshop 2022 MANIQA: Multi-dimension Attention Network for No-Reference Image Quality Assessment Sidi Yang, Tianhe Wu, Shuwei Shi, Shanshan Lao, Yuan Gong, Mingdeng Cao, Jiahao Wang, Yujiu Yang CVPR Workshop (Oral Presentation), 2022 arXiv / Code The champion method for NTIRE2022 NR IQA.

Internship

	YLab, OPPO Research Institute Research Intern, focus on VLM for low-level visual understanding and perception Supervisor: Prof. Lei Zhang	Apr. 2024 - Present
	Department of Computer Science, City University of Hong Kong Research Assistant, focus on low-level vision Supervisor: Prof. Kede Ma	Dec. 2023 - Aug. 2025

Last updated: May 2025
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