Huang, Kaizhu

43 publications

CVPR 2025 BFANet: Revisiting 3D Semantic Segmentation with Boundary Feature Analysis Weiguang Zhao, Rui Zhang, Qiufeng Wang, Guangliang Cheng, Kaizhu Huang

NeurIPS 2025 Can MLLMs Absorb Math Reasoning Abilities from LLMs as Free Lunch? Yijie Hu, Zihao Zhou, Kaizhu Huang, Xiaowei Huang, Qiufeng Wang

WACV 2025 Covariance-Based Space Regularization for Few-Shot Class Incremental Learning Yijie Hu, Guanyu Yang, Zhaorui Tan, Xiaowei Wang, Kaizhu Huang, Qiu-Feng Wang

AAAI 2025 Disentangling Tabular Data Towards Better One-Class Anomaly Detection Jianan Ye, Zhaorui Tan, Yijie Hu, Xi Yang, Guangliang Cheng, Kaizhu Huang

AAAI 2025 GNS: Solving Plane Geometry Problems by Neural-Symbolic Reasoning with Multi-Modal LLMs Maizhen Ning, Zihao Zhou, Qiufeng Wang, Xiaowei Huang, Kaizhu Huang

ICLR 2025 Is Your Model Really a Good Math Reasoner? Evaluating Mathematical Reasoning with Checklist Zihao Zhou, Shudong Liu, Maizhen Ning, Wei Liu, Jindong Wang, Derek F. Wong, Xiaowei Huang, Qiufeng Wang, Kaizhu Huang

CVPR 2025 KMD: Koopman Multi-Modality Decomposition for Generalized Brain Tumor Segmentation Under Incomplete Modalities Tianyi Liu, Haochuan Jiang, Kaizhu Huang

CVPR 2025 PO3AD: Predicting Point Offsets Toward Better 3D Point Cloud Anomaly Detection Jianan Ye, Weiguang Zhao, Xi Yang, Guangliang Cheng, Kaizhu Huang

AAAI 2025 Template-Driven LLM-Paraphrased Framework for Tabular Math Word Problem Generation Xiaoqiang Kang, Zimu Wang, Xiaobo Jin, Wei Wang, Kaizhu Huang, Qiufeng Wang

AAAI 2025 Towards Better Robustness Against Natural Corruptions in Document Tampering Localization Huiru Shao, Kaizhu Huang, Wei Wang, Xiaowei Huang, Qiufeng Wang

ICCV 2025 Towards a Universal 3D Medical Multi-Modality Generalization via Learning Personalized Invariant Representation Zhaorui Tan, Xi Yang, Tan Pan, Tianyi Liu, Chen Jiang, Xin Guo, Qiufeng Wang, Anh Nguyen, Yuan Qi, Kaizhu Huang, Yuan Cheng

ICLR 2025 ZeroDiff: Solidified Visual-Semantic Correlation in Zero-Shot Learning Zihan Ye, Shreyank N Gowda, Shiming Chen, Xiaowei Huang, Haotian Xu, Fahad Shahbaz Khan, Yaochu Jin, Kaizhu Huang, Xiaobo Jin

ECCV 2024 Delving into Adversarial Robustness on Document Tampering Localization Huiru Shao, Zhuang Qian, Kaizhu Huang, Wei Wang, Xiaowei Huang, Qiufeng Wang

TMLR 2024 Improving Robust Generalization with Diverging Spanned Latent Space Owen Dou, Zhiqiang Gao, Hangchi Shen, Ziling Yuan, Shufei Zhang, Kaizhu Huang

NeurIPS 2024 Interpret Your Decision: Logical Reasoning Regularization for Generalization in Visual Classification Zhaorui Tan, Xi Yang, Qiufeng Wang, Anh Nguyen, Kaizhu Huang

AAAI 2024 MathAttack: Attacking Large Language Models Towards Math Solving Ability Zihao Zhou, Qiufeng Wang, Mingyu Jin, Jie Yao, Jianan Ye, Wei Liu, Wei Wang, Xiaowei Huang, Kaizhu Huang

CVPR 2024 Rethinking Multi-Domain Generalization with a General Learning Objective Zhaorui Tan, Xi Yang, Kaizhu Huang

AAAI 2024 Semantic-Aware Data Augmentation for Text-to-Image Synthesis Zhaorui Tan, Xi Yang, Kaizhu Huang

AAAI 2024 Unraveling Batch Normalization for Realistic Test-Time Adaptation Zixian Su, Jingwei Guo, Kai Yao, Xi Yang, Qiufeng Wang, Kaizhu Huang

ICCV 2023 Divide and Conquer: 3D Point Cloud Instance Segmentation with Point-Wise Binarization Weiguang Zhao, Yuyao Yan, Chaolong Yang, Jianan Ye, Xi Yang, Kaizhu Huang

AAAI 2023 Rethinking Data Augmentation for Single-Source Domain Generalization in Medical Image Segmentation Zixian Su, Kai Yao, Xi Yang, Kaizhu Huang, Qiufeng Wang, Jie Sun

MLJ 2023 Robust Generative Adversarial Network Shufei Zhang, Zhuang Qian, Kaizhu Huang, Rui Zhang, Jimin Xiao, Yuan He, Canyi Lu

ICCV 2023 Towards Better Robustness Against Common Corruptions for Unsupervised Domain Adaptation Zhiqiang Gao, Kaizhu Huang, Rui Zhang, Dawei Liu, Jieming Ma

ECCV 2022 Outpainting by Queries Kai Yao, Penglei Gao, Xi Yang, Jie Sun, Rui Zhang, Kaizhu Huang

MLJ 2022 Re-Thinking Model Robustness from Stability: A New Insight to Defend Adversarial Examples Shufei Zhang, Kaizhu Huang, Zenglin Xu

NeurIPS 2021 Global-Aware Beam Search for Neural Abstractive Summarization Ye Ma, Zixun Lan, Lu Zong, Kaizhu Huang

ICCV 2021 Gradient Distribution Alignment Certificates Better Adversarial Domain Adaptation Zhiqiang Gao, Shufei Zhang, Kaizhu Huang, Qiufeng Wang, Chaoliang Zhong

ICML 2021 Towards Better Robust Generalization with Shift Consistency Regularization Shufei Zhang, Zhuang Qian, Kaizhu Huang, Qiufeng Wang, Rui Zhang, Xinping Yi

ECCV 2020 Feature Representation Matters: End-to-End Learning for Reference-Based Image Super-Resolution Yanchun Xie, Jimin Xiao, Mingjie Sun, Chao Yao, Kaizhu Huang

ECML-PKDD 2020 Inductive Generalized Zero-Shot Learning with Adversarial Relation Network Guanyu Yang, Kaizhu Huang, Rui Zhang, John Yannis Goulermas, Amir Hussain

AAAI 2020 Reliability Does Matter: An End-to-End Weakly Supervised Semantic Segmentation Approach Bingfeng Zhang, Jimin Xiao, Yunchao Wei, Mingjie Sun, Kaizhu Huang

ICLR 2020 Robust Generative Adversarial Network Shufei Zhang, Zhuang Qian, Kaizhu Huang, Jimin Xiao, Yuan He

AAAI 2020 Towards Better Forecasting by Fusing near and Distant Future Visions Jiezhu Cheng, Kaizhu Huang, Zibin Zheng

ICCVW 2019 Beyond Attributes: High-Order Attribute Features for Zero-Shot Learning Xiao-Bo Jin, Guo-Sen Xie, Kaizhu Huang, Jianyu Miao, Qiufeng Wang

ECML-PKDD 2013 Fast kNN Graph Construction with Locality Sensitive Hashing Yan-Ming Zhang, Kaizhu Huang, Guanggang Geng, Cheng-Lin Liu

MLJ 2013 Geometry Preserving Multi-Task Metric Learning Peipei Yang, Kaizhu Huang, Cheng-Lin Liu

ECML-PKDD 2012 Geometry Preserving Multi-Task Metric Learning Peipei Yang, Kaizhu Huang, Cheng-Lin Liu

IJCAI 2011 Pattern Field Classification with Style Normalized Transformation Xu-Yao Zhang, Kaizhu Huang, Cheng-Lin Liu

UAI 2010 Robust Metric Learning by Smooth Optimization Kaizhu Huang, Rong Jin, Zenglin Xu, Cheng-Lin Liu

NeurIPS 2009 Sparse Metric Learning via Smooth Optimization Yiming Ying, Kaizhu Huang, Colin Campbell

CVPR 2004 Learning Classifiers from Imbalanced Data Based on Biased Minimax Probability Machine Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu

ICML 2004 Learning Large Margin Classifiers Locally and Globally Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu

JMLR 2004 The Minimum Error Minimax Probability Machine Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, Laiwan Chan