About Me

I am currently an Assistant Professor and AI researcher at Osaka University. I received my doctoral degree from Xiamen University. My research interests are computer vision and machine learning, especially in AI safety/reliability, deep learning, multimodal ML, AI Ethics, and large-scale image retrieval.

Publications

AI Safty/Reliability/Ethics

• Hong Liu, Zhun Zhong, Nicu Sebe, Shin’ichi Satoh. Mitigating Robust Overfitting via Self-Residual-Calibration Regularization. Artificial Intelligence, 2023. [CODES] (Also with IJCAI Journal Track, 2024)
• Hong Liu, Yongqing Sun, Yukihiro Bandoh, Masaki Kitahara, Shin’ichi Satoh. Deep Counterfactual Representation Learning for Visual Recognition against Weather Corruptions. IEEE Transactions on Multimedia, 2023.
• Hong Liu. Revisiting and Advancing Adversarial Training Through A Simple Baseline. In Arxiv, 2023.
• Hong Liu, Yongqing Sun, Shin’ichi Satoh. Rethinking Robust 3D Recognition via Multi-view Test-Time Adaptation. 画像の認識・理解シンポジウム (MIRU), 2023.
• Hong Liu, Rongrong Ji, Jie Li, Baochang Zhang, Yue Gao, Yongjian Wu, Feiyue Huang. Universal Adversarial Perturbation via Prior Driven Uncertainty Approximation. ICCV, 2019. (Oral). [CODES]
• Hong Liu and Yitong Lu. DoubleCCA: Improving Foundation Model Group Robustness with Random Sentence Embeddings. In Arxiv, 2024.
• Hao Zhang, Wenqi Shao, Hong Liu, Yongqiang Ma, Ping Luo, Yu Qiao, Kaipeng Zhang. AVIBench: Towards Evaluating the Robustness of Large Vision-Language Model on Adversarial Visual-Instructions, IEEE TIFS, 2024.
• Yue Yang, Yuqi lin, Hong Liu, Wenqi Shao, Runjian Chen, Hailong Shang, Yu Wang, Yu Qiao, Kaipeng Zhang, Ping Luo. Towards Implicit Prompt For Text-To-Image Models. ICML, 2024. [Project]
• Huafeng Kuang, Hong Liu#, Xianming Liu, Rongrong Ji. Defense Against Adversarial Attacks Using Topology Aligning Adversarial Training. IEEE Trans. on Information Forensics and Security, 2024. (# Corresponding Author)
• Huafeng Kuang, Hong Liu#, Yongjian Wu, Shin’ichi Satoh, Rongrong Ji. Improving Adversarial Robustness via Information Bottleneck Distillation. NeurIPS, 2023. [CODES] (# Project lead)
• Huafeng Kuang, Hong Liu, Yongjian Wu, Rongrong Ji. Semantically Consistent Visual Representation for Adversarial Robustness. IEEE Trans. on Information Forensics and Security, 2023.
• Fengxiang Yang, Juanjuan Weng, Zhun Zhong, Hong Liu, Zheng Wang, Zhiming Luo, Donglin Cao, Shaozi Li, Shin’ichi Satoh, Nicu Sebe. Towards Robust Person Re-identification by Defending Against Universal Attackers. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2022. [CODES]
• Yixu Wang, Jie Li, Hong Liu, Yan Wang, Mingliang Xu, Yongjian Wu, Rongrong Ji. Model Stealing Attack based on Sampling and Weighting. SCIENCE CHINA Information Sciences, 2022. (In Chinese)
• Yixu Wang, Jie Li, Hong Liu, Yan Wang, Yongjian Wu, Feiyue Huang, Rongrong Ji. Black-Box Dissector: Towards Erasing-based Hard-Label Model Stealing Attack. ECCV, 2022. [CODES]
• Xinshuai Dong, Anh Tuan Luu, Rongrong Ji, Hong Liu. Towards Robustness Against Natural Language Word Substitutions. ICLR 2021. (Spotlight) [CODES]
• Fengxiang Yang, Zhun Zhong Hong Liu, Zheng Wang, Zhiming Luo, Shaozi Li, Nicu Sebe, Shin’ichi Satoh, Learning to Attack Real-World Models for Person Re-identification via Virtual-Guided Meta-Learning. AAAI 2021.[CODES]
• Liujuan Cao, Huafeng Kuang, Hong Liu, Yan Wang, Baochang Zhang, Feiyue Huang, Yongjian Wu, Rongrong Ji. Towards Robust Adversarial Training via Geometry Constraint and Dual label Supervised. Journal of Software, 2021. [Chinese Version][English Version] [CODES]
• Xinshuai Dong, Hong Liu, Liujuan Cao, Rongrong Ji, Qixiang Ye, Jianzhuang Liu, Qi Tian. API-Net: Robust Generative Classifier via a Single Discriminator. ECCV 2020.[CODES]
• Hanlin Chen, Baochang Zhang, Song Xue, Xuan Gong, Hong Liu, Rongrong Ji, David Doermann. Anti-Bandit Neural Architecture Search for Model Defense. ECCV 2020.[CODES]
• Jie Li, Rongrong Ji, Hong Liu, Jianzhuang Liu, Bineng Zhong, Cheng Deng, Qi Tian. Projection & Probability-Driven Black-Box Attack. CVPR, 2020.[CODES]
• Jie Li, Rongrong Ji, Hong Liu, Xiaopeng Hong, Yue Gao, Qi Tian. Universal Perturbation Attack Against Image Retrieval. ICCV, 2019. [CODES]

Robust Visual Recognition

• Ke Sun, Zhongxi Chen, Xianming Lin, Xiaoshuai Sun, Hong Liu#, Rongrong Ji. Conditional Diffusion Models for Camouflaged and Salient Object Detection. IEEE TPAMI, 2025. [CODES] (# Corresponding Author)
• Ke Sun, Shen Chen, Taiping Yao, Hong Liu#, Xiaoshuai Sun, Shouhong Ding, Rongrong Ji. DiffusionFake: Enhancing Generalization in Deepfake Detection via Guided Stable Diffusion. NeurIPS, 2024. [CODES] (# Corresponding Author)
• Zhenglin Zhou#, Huaxia Li#, Hong Liu#, Nanyang Wang, Gang Yu, Rongrong Ji. STAR Loss: Reducing Semantic Ambiguity in Facial Landmark Detection. CVPR, 2023. [CODES] (# contribute equally)
• Hong Liu, Jie Li, Rongrong Ji, Yongjian Wu. Learning Neural Bag-of-Matrix-Summarization with Riemannian Network. AAAI, 2019. [CODES]
• Zhengwei Yang, Xian Zhong, Zhun Zhong, Hong Liu, Zheng Wang, Shin’ichi Satoh. Win-Win by Competition: Auxiliary-Free Cloth-Changing Person Re-Identification. IEEE Trans. on Image Processing, 2023. [CODES]
• Zhengwei Yang, Xian Zhong, Hong Liu, Zhun Zhong, Zheng Wang. Attentive Decoupling Network for Cloth-Changing Re-identification. ICME, 2022.
• Ke Sun, Hong Liu, Taiping Yao, Xiaoshuai Sun, Shen Chen, Shouhong Ding, Rongrong Ji. An Information Theoretic Approach for Attention-Driven Face Forgery Detection. ECCV, 2022. [CODES]
• Nobukatsu Kajiura, Hong Liu, Shin’ichi Satoh. Improving Camouflaged Object Detection with the Uncertainty of Pseudo-edge Labels. ACM MM Asia, 2021. [CODES]
• Ke Sun, Hong Liu, Qixiang Ye, Yue Gao, Jianzhuang Liu, Ling Shao, Rongrong Ji. Domain General Face Forgery Detection by Learning to Weight. AAAI 2021. [CODES]
• Huafeng Kuang, Rongrong Ji, Hong Liu, Shengchuan Zhang, Xiaoshuai Sun, Feiyue Huang, Baochang Zhang. Multi-modal Multi-layer Fusion Network with Average Binary Center Loss for Face Anti-spoofing. ACM MM, 2019. [CODES]

Fast Nearest Neighbour Search

• Hong Liu. Sparse-Inductive Generative Adversarial Hashing for Nearest Neighbor Search. In Arxiv 2023.
• Hong Liu, Rongrong Ji, Jingdong Wang, Chunhua Shen. Ordinal Constraint Binary Coding for Approximate Nearest Neighbor Search. IEEE Trans. on Pattern Analysis and Machine Intelligence. Volume: 41, Issue: 4, 2019.
• Hong Liu, Mingbao Lin, Shengchuan Zhang, Yongjian Wu, Feiyue Huang, Rongrong Ji. Dense Auto-Encoder Hashing for Robust Cross-Modality Retrieval. ACM MM, 2018. [CODES]
• Rongrong Ji; Hong Liu#; Liujuan Cao; Di Liu; Yongjian Wu, Feiyue Huang. Towards Optimal Manifold Hashing via Discrete Locally Linear Embedding, IEEE Trans. on Image Processing, Volume 26, Issue 11, 2017. [CODES] (# Corresponding Author)
• Hong Liu, Rongrong Ji, Yongjian Wu, Feiyue Huang, Baochang Zhang. Cross-Modality Binary Code Learning via Fusion Similarity Hashing. CVPR, 2017. [CODES]
• Hong Liu, Rongrong Ji, Yongjian Wu, Feiyue Huang. Ordinal Constrained Binary Code Learning for Nearest Neighbor Search. AAAI, 2017. (Oral) [CODES]
• Hong Liu, Rongrong Ji, Yongjian Wu, Gang Hua. Supervised Matrix Factorization for Cross-Modality Hashing. IJCAI, 2016. [CODES]
• Hong Liu, Rongrong Ji, Yongjian Wu, Wei Liu. Towards Optimal Binary Code Learning via Ordinal Embedding. AAAI, 2016. [CODES]
• Hong Liu, Aiwen Jiang, Mingwen Wang, Jianyi Wan.Local Similarity Preserved Hashing Learning via Markov Graph for Efficient Similarity Search. Neurocomputing, 159, 2015.
• Mingbao Lin, Rongrong Ji, Hong Liu, Xiaoshuai Sun, Shen Chen, Qi Tian. Hadamard Matrix Guided Online Hashing. International Journal of Computer Vision, 2020. [CODES]
• Jie Hu, Rongrong Ji, Hong Liu, Shengchuan Zhang, Cheng Deng, Qi Tian. Towards Visual Feature Translation. CVPR, 2019. [CODES]
• Mingbao Lin, Rongrong Ji, Hong Liu, Xiaoshuai Sun, Yongjian Wu, Yunsheng Wu. Towards Optimal Discrete Online Hashing with Balanced Similarity. AAAI, 2019. [CODES]
• Mingbao Lin, Rongrong Ji, Hong Liu, Yongjian Wu. Supervised Online Hashing via Hadamard Codebook Learning. ACM MM, 2018. (Oral). [CODES]
• Jianqiang Qian, Xianmin Lin, Hong Liu, Youming Deng, Rongrong Ji. Towards Compact Visual Descriptor via Deep Fisher Network with Binary Embedding. ICME, 2018. (Oral)

Other Topics

• Hong Liu, Yuta Nakashima, Noboru Babaguchi. Paladin: Understanding Video Intentions in Political Advertisement Videos. WACV 2025.
• Eisei Nakahara, Hong Liu, Qiong Chang, Xian-hua Han. Deep Dual Internal Learning for Hyperspectral Image Super-Resolution. MMM 2025.
• Antoine Gratia, Hong Liu, Shin’ichi Satoh, Paul Temple, Pierre-Yves Schobbens, Gilles Perrouin. CNNGen: A Generator and a Dataset for Energy-Aware Neural Architecture Search. ESANN 2024.
• Zelong Zeng, Fan Yang, Hong Liu#, Shin’ichi Satoh. Self-distillation with Online Diffusion on Batch Manifolds Improves Deep Metric Learning. Viusal Intelligence, 2024. [CODES] (# Corresponding Author)
• Deng-Ping Fan, Ziling Huang, Peng Zheng, Hong Liu#, Xuebin Qin, Luc Van Gool. Deep Facial Synthesis: A New Challenge. Machine Intelligence Research, 2022. [CODES] [DATA] [ToolBox] [Awesome-List] [Chinese Version] [Video in Chinese] [SLIDES(code:eoa3)] (# Corresponding Author)
• Xiao Liu, Shengchuan Zhang, Hong Liu, Xin Liu, Cheng Deng, Rongrong Ji. CerfGAN: A Compact, Effective, Robust, and Fast Model for Unsupervised Multi-Domain Image-to-Image Translation. In Arxiv, 2018.

Honors and Awards

• Notable Reviewer, ICLR 2023

• Top-100 Chinese New Stars in Artificial Intelligence by Baidu Scholar, China, 2021

• Japan Society for the Promotion of Science (JSPS) Fellowship, Japan, 2020

• CSIG Outstanding Doctoral Dissertation Award, China Society of Image and Graphics (CSIG), China, 2020

• Fujian Outstanding Doctoral Dissertation Award, Fujian, China, 2020

• Outstanding Ph.D. Graduate Student, Xiamen University, China, 2020

Activities

• Associate Editor: Visual Intelligence

• Guest Editor: IJCV, Electronic, …

• Conference Organizer: CVPR 2025 Workshop

• Area Chair: ACM MM, …

• Journal Reviewer: IEEE TPAMI, IJCV, IEEE TIP, IEEE TIFS, IEEE TMM, …

• Conference reviewer: ICLR, ICML, NeurIPS, CVPR, ICCV, ECCV, IJCAI, AAAI, ACM MM, …

Contact

E-mail: lynnliu.xmu[AT]gmail.com or hliu[AT]ids.osaka-u.ac.jp

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