Zhihe Lu (Lucas)

Zhihe Lu (卢治合)

Currently, I am a Postdoc researcher at National University of Singapore, working with Prof. Xinchao Wang. Before, I finished the PhD degree at University of Surrey under the supervision of Prof. Tao Xiang and Prof. Yi-Zhe Song. and the Master's degree at the Institute of Automation, Chinese Academy of Sciences, supervised by Prof. Ran He.

My research interest centers around the following areas:
Computer Vision: Object Recognition and Semantic Segmentation
Transfer Learning: Unsupervised Domain Adaptation, Source-free Domain Adaptation and Test-time Adaptation
Few-shot Learning: Meta-learning and Generalized Few-shot Models
Effcient Tuning of Foundation Models: Effcient Tuning of Vision-Language Models

Email / CV / Google Scholar / Github

News

2024.09.26: One paper accepted on NeurIPS 2024.
2024.07.16: Two papers accepted on ACM MM 2024.
2024.07.01: Two papers accepted on ECCV 2024.
2024.06.10: Gave a talk on ACM ICMR 2024.
2024.05.02: One paper accepted on ICML 2024.
2024.04.21: One paper accepted on PR 2024.
2023.09.22: Two papers accepted on NeurIPS 2023.
2023.07.11: One paper accepted on TIP 2023.
2023.05.26: One paper accepted on TIP 2023.
2023.02.28: One paper accepted on CVPR 2023.

Selected Publications

	Beyond Sole Strength: Customized Ensembles for Generalized Vision-Language Models Zhihe Lu, Jiawang Bai, Xin Li, Zeyu Xiao, Xinchao Wang ICML, 2024 code The first investigation of ensemble learning for VLMs.
	GraphAdapter: Tuning Vision-Language Models With Dual Knowledge Graph Xin Li^, Dongze Lian^, Zhihe Lu^, Jiawang Bai, Zhibo Chen, Xinchao Wang Equal Contribution NeurIPS, 2023 code Introduce knowledge graph for tuning vision and language models.
	Frequency-enhanced Data Augmentation for Vision-and-Language Navigation Keji He, Chenyang Si, Zhihe Lu, Yan Huang, Liang Wang, Xinchao Wang NeurIPS, 2023 code A work to explore the significance of high-frequency information for enhanced Vision-and-Language Navigation.
	Uncertainty-aware Source-free Domain Adaptive Semantic Segmentation Zhihe Lu, Da Li, Yi-Zhe Song, Tao Xiang, Timothy M. Hospedales TIP, 2023 An uncertainty-aware solution for SFDASS.
	Prediction Calibration for Generalized Few-shot Semantic Segmentation Zhihe Lu, Sen He, Da Li, Yi-Zhe Song, Tao Xiang TIP, 2023 Investigating the feature-prediction covariance based Transformer for calibrating the biases in GFSS.
	Task Residual for Tuning Vision-Language Models Tao Yu^, Zhihe Lu^, Xin Jin, Zhibo Chen, Xinchao Wang * Equal Contribution CVPR, 2023 code A simple yet effective tuning method for vision and language models.
	Simpler is Better: Few-shot Semantic Segmentation with Classifier Weight Transformer Zhihe Lu, Sen He, Xiatian Zhu, Li Zhang, Yi-Zhe Song, Tao Xiang ICCV, 2021 code A novel training pipeline for few-shot segmentation with classifier weight transformer.
	Stochastic Classifiers for Unsupervised Domain Adaptation Zhihe Lu, Yongxin Yang, Xiatian Zhu, Cong Liu, Yi-Zhe Song, Tao Xiang CVPR, 2020 code A novel way to use infinite number of classifiers without extra parameters to identify misaligned regions.
	Conditional Expression Synthesis with Face Parsing Transformation Zhihe Lu, Tanhao Hu, Lingxiao Song, Zhaoxiang Zhang, Ran He ACM MM, 2018 A Couple-Agent Face Parsing based Generative Adversarial Network (CAFP-GAN) that unites the knowledge of facial semantic regions and controllable expression signals.
	Geometry Guided Adversarial Facial Expression Synthesis Lingxiao Song, Zhihe Lu, Ran He, Zhenan Sun, Tieniu Tan ACM MM, 2018 A Geometry-Guided Generative Adversarial Network (G2-GAN) was proposed for photorealistic and identity-preserving facial expression synthesis.
	Recent Progress of Face Image Synthesis Zhihe Lu, Zhihang Li, Jie Cao, Ran He, Zhenan Sun ACPR, 2017 A very early survey for face image synthesis.

Service

Reviewers: TPAMI, IJCV, TIP, CVPR, ICCV, ECCV, ICML, NeurIPS, ICLR, etc.

Thanks for Jon Barron's website sharing.