Dec 2, 2024 |
Get Confused Cautiously: Textual Sequence Memorization Erasure with Selective Entropy Maximization
Zhaohan Zhang, Ziquan Liu, Ioannis Patras accepted at COLING 2025.
|
Dec 1, 2024 |
Joined the European Lab For Learning & Intelligent Systems (ELLIS) as a Fellow.
|
Nov 27, 2024 |
“Enhancing Zero-Shot Facial Expression Recognition by LLM Knowledge Transfer”, Zengqun Zhao, Yu Cao, Shaogang Gong, Ioannis Patras, accepted at WACV 2025
|
Nov 25, 2024 |
1 PhD position available (funded by a China Scholarship Council scholarship in collaboration with Dr. Georgios (Yorgos) Tzimiropoulos) in the area of Multimodal Machine Learning and AI. Topics include Generative AI and Vision Language models, for image and video analysis and understanding (e.g, VQA) and Generative AI (e.g., diffusion models) for image/video generation and editing. Please see here for more details.
|
Oct 22, 2024 |
2 papers accepted at NeurIPS 2024! 1) Multilinear Mixture of Experts: Scalable Expert Specialization through Factorization, James Oldfield, Markos Georgopoulos, Grigorios G. Chrysos, Christos Tzelepis, Yannis Panagakis, Mihalis A. Nicolaou, Jiankang Deng, Ioannis Patras. (code), 2) CemiFace: Center-based Semi-hard Synthetic Face Generation for Face Recognition, Zhonglin Sun, Siyang Song, Ioannis Patras, Georgios Tzimiropoulos. (code)
|
Jul 15, 2024 |
CLIPCleaner: Cleaning Noisy Labels with CLIP
Chen Feng, Georgios Tzimiropoulos, Ioannis Patras accepted at ACMMM 2024.
|
Jul 11, 2024 |
NoiseBox: Towards More Efficient and Effective Learning with Noisy Labels, Chen Feng, Georgios Tzimiropoulos, Ioannis Patras accepted at TCSVT.
|
Jul 1, 2024 |
Efficient Unsupervised Visual Representation Learning with Explicit Cluster Balancing
Ioannis Maniadis Metaxas, Georgios Tzimiropoulos, Ioannis Patras accepted at ECCV 2024.
|
Jun 26, 2024 |
Bilinear Models of Parts and Appearances in Generative Adversarial Networks, James Oldfield, Christos Tzelepis, Yannis Panagakis, Mihalis A. Nicolaou, Ioannis Patras accepted at TPAMI
|
Mar 7, 2024 |
2 papers accepted at CVPR 2024: 1) LAFS: Landmark-based Facial Self-supervised Learning for Face Recognition, Zhonglin Sun, Chen Feng, Ioannis Patras and Georgios Tzimiropoulos; 2) Self-Supervised Facial Representation Learning with Facial Region Awareness, Zheng Gao, Ioannis Patras
|
Nov 20, 2023 |
Improving Fairness using Vision-Language Driven Image Augmentation, Moreno D’Incà, Christos Tzelepis, Ioannis Patras, Nicu Sebe, accepted at WACV 2024.
|
Nov 10, 2023 |
“A Simple Baseline for Knowledge-Based Visual Question Answering”, Alexandros Xenos, Themos Stafylakis, Ioannis Patras, and Georgios Tzimiropoulos, accepted at EMNLP 2023
|
Nov 8, 2023 |
Self-Supervised Representation Learning with Cross-Context Learning between Global and Hypercolumn Features, Zheng Gao, Chen Feng, Ioannis Patras, accepted at WACV 2024.
|
Nov 8, 2023 |
Improving Fairness using Vision-Language Driven Image Augmentation, Moreno D’Incà, Christos Tzelepis, Ioannis Patras, Nicu Sebe, accepted at WACV 2024.
|
Sep 22, 2023 |
Parts of Speech-Grounded Subspaces in Vision-Language Models James Oldfield and Christos Tzelepis and Yannis Panagakis and Mihalis A. Nicolaou and Ioannis Patras accepted at NeurIPS 2023
|
Aug 21, 2023 |
“Prompting Visual-Language Models for Dynamic Facial Expression Recognition”, Zengqun Zhao, Ioannis Patras, accepted at BMVC 2023
|
Jul 14, 2023 |
HyperReenact: One-Shot Reenactment via Jointly Learning to Refine and Retarget Faces, Stella Bounareli, Christos Tzelepis, Vasileios Argyriou, Ioannis Patras, Georgios Tzimiropoulos, accepted at ICCV 2023
|
Mar 17, 2023 |
3 papers accepted at CVPR 2023 (one top-10%)
|
Feb 28, 2023 |
Invited talk at International AI Doctoral Academy (AIDA) on Generative Models: Controllable Generation and Learning (abstract and video)
|
Feb 1, 2023 |
PandA: Unsupervised Learning of Parts and Appearances in the Feature Maps of GANs, James Oldfield, Christos Tzelepis, Yannis Panagakis, Mihalis A. Nicolaou, Ioannis Patras accepted at ICLR 2023
|
Jan 19, 2023 |
Call-for-Papers: ACM TOMM SI on Realistic Synthetic Data: Generation, Learning, Evaluation
|