News
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2024.7
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One paper been accepted to ACM MM'2024!
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2024.7
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One paper been accepted to IEEE Transactions on Circuits and Systems for Video Technology!
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2024.5
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I have passed my PhD defence in 10th May! Many thanks to the examiners: Dr. Qianni Zhang and
Prof. Tao Xiang.
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2024.2
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LAFS been accepted to CVPR'2024!
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2024.1
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I was invited for an open seminar talk
in RIKEN AIP.
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Research
I'm interested in various weakly supervised learning problems in the context of computer vision, including
completely unlabelled self-supervised learning, semi-supervised learning with partial data having labels, and learning with noisy/coarse labels.
I'm happy to discuss any related topics and possible collaborations, please simply drop me an email!
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CLIPCleaner: Cleaning Noisy Labels with CLIP
Chen Feng, Georgios Tzimiropoulos, Ioannis Patras
ACMMM, 2024
code
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paper
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NoiseBox: Towards More Efficient and Effective Learning with Noisy Labels
Chen Feng, Georgios Tzimiropoulos, Ioannis Patras
TCSVT, 2024
paper
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LAFS: Landmark-based Facial Self-supervised Learning for Face Recognition
Zhonglin Sun, Chen Feng, Ioannis Patras, Georgios Tzimiropoulos
CVPR, 2024
code
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paper
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Self-Supervised Representation Learning with Cross-Context Learning between Global and Hypercolumn Features
Zheng Gao,
Chen Feng,
Ioannis Patras
WACV, 2024
code
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paper
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MaskCon: Masked Contrastive Learning for Coarse-Labeled Dataset
Chen Feng,
Ioannis Patras
CVPR, 2023
code
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paper
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video
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SSR: An Efficient and Robust Framework for Learning with Unknown Label Noise
Chen Feng,
Georgios Tzimiropoulos,
Ioannis Patras
BMVC, 2022
code
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paper
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Adaptive Soft Contrastive Learning
Chen Feng,
Ioannis Patras
ICPR, 2022
code
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paper
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Academic service
Conferences: ICML2022(Outstanding Reviewer), CVPR2023-2024, NeurIPS2022-2024, AAAI2023-2024, ICLR2023-2025, ICCV2023, ECCV2024, AISTATS2025, BMVC2022, ACCV2024, ICPR2024
Journals: IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Circuits and Systems for Video Technology, Image and Vision Computing
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