Zhihe Lu
Orcid: 0000-0002-6917-8654
According to our database1,
Zhihe Lu
authored at least 21 papers
between 2016 and 2024.
Collaborative distances:
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Bibliography
2024
Revisiting Self-Supervised Heterogeneous Graph Learning from Spectral Clustering Perspective.
CoRR, 2024
P-BiC: Ultra-High-Definition Image Moiré Patterns Removal via Patch Bilateral Compensation.
Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024
Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Parameter-Efficient and Memory-Efficient Tuning for Vision Transformer: A Disentangled Approach.
Proceedings of the Computer Vision - ECCV 2024, 2024
Dual-Path Adversarial Lifting for Domain Shift Correction in Online Test-Time Adaptation.
Proceedings of the Computer Vision - ECCV 2024, 2024
2023
IEEE Trans. Image Process., 2023
IEEE Trans. Image Process., 2023
CoRR, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
2021
Simpler is Better: Few-shot Semantic Segmentation with Classifier Weight Transformer.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021
2020
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020
2018
Proceedings of the 2018 ACM Multimedia Conference on Multimedia Conference, 2018
Proceedings of the 2018 ACM Multimedia Conference on Multimedia Conference, 2018
2017
Proceedings of the 4th IAPR Asian Conference on Pattern Recognition, 2017
2016
Proceedings of the 2016 IEEE International Conference on Digital Signal Processing, 2016