Wolf, Lior

DeepFace: Closing the Gap to Human-Level Performance in Face Verification

Taigman, Y., Yang, M., Ranzato, M., & Wolf, L. (2014) · 2014 IEEE Conference on Computer Vision and Pattern Recognition

Face recognition and analysisFace and Expression Recognition

Cited by 6,542

Robust Object Recognition with Cortex-Like Mechanisms

Serre, T., Wolf, L., Bileschi, S., Riesenhuber, M., & Poggio, T. (2007) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Advanced Image and Video Retrieval TechniquesAdvanced Neural Network Applications

Cited by 1,667

Transformer Interpretability Beyond Attention Visualization

Chefer, H., Gur, S., & Wolf, L. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Explainable Artificial Intelligence (XAI)Advanced Neural Network Applications

Cited by 903

Attend-and-Excite: Attention-Based Semantic Guidance for Text-to-Image Diffusion Models

Chefer, H., Alaluf, Y., Vinker, Y., Wolf, L., & Cohen-Or, D. (2023) · ACM Transactions on Graphics

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 461

Chest pathology detection using deep learning with non-medical training

Bar, Y., Diamant, I., Wolf, L., Lieberman, S., Konen, E., & Greenspan, H. (2015) · 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI)

COVID-19 diagnosis using AIRadiomics and Machine Learning in Medical Imaging

Cited by 392

Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers

Chefer, H., Gur, S., & Wolf, L. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Explainable Artificial Intelligence (XAI)Multimodal Machine Learning Applications

Cited by 313

DeepFake Detection Based on Discrepancies Between Faces and Their Context

Nirkin, Y., Wolf, L., Keller, Y., & Hassner, T. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Digital Media Forensic DetectionFace recognition and analysis

Cited by 312

SegDiff: Image Segmentation with Diffusion Probabilistic Models

Amit, T., Shaharbany, T., Nachmani, E., & Wolf, L. (2021) · arXiv

Advanced Neural Network ApplicationsMedical Image Segmentation Techniques

Cited by 179

Relative Attributing Propagation: Interpreting the Comparative Contributions of Individual Units in Deep Neural Networks

Nam, W.-J., Gur, S., Choi, J., Wolf, L., & Lee, S.-W. (2020) · Proceedings of the AAAI Conference on Artificial Intelligence

Explainable Artificial Intelligence (XAI)Advanced Neural Network Applications

Cited by 98

DeepChess: End-to-End Deep Neural Network for Automatic Learning in Chess

David, O. E., Netanyahu, N. S., & Wolf, L. (2016) · Lecture Notes in Computer Science

Artificial Intelligence in GamesArtificial Intelligence Applications

Cited by 76

Training-Free Consistent Text-to-Image Generation

Tewel, Y., Kaduri, O., Gal, R., Kasten, Y., Wolf, L., Chechik, G., & Atzmon, Y. (2024) · ACM Transactions on Graphics

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 68

Diverse and Aligned Audio-to-Video Generation via Text-to-Video Model Adaptation

Yariv, G., Gat, I., Benaim, S., Wolf, L., Schwartz, I., & Adi, Y. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 59

Noise Estimation for Generative Diffusion Models

San-Roman, R., Nachmani, E., & Wolf, L. (2021) · arXiv

Generative Adversarial Networks and Image SynthesisImage and Signal Denoising Methods

Cited by 44

Visualization of Supervised and Self-Supervised Neural Networks via Attribution Guided Factorization

Gur, S., Ali, A., & Wolf, L. (2020) · arXiv

Explainable Artificial Intelligence (XAI)Advanced Neural Network Applications

Cited by 34

A theoretical framework for deep transfer learning

Galanti, T., Wolf, L., & Hazan, T. (2016) · Information and Inference

Domain Adaptation and Few-Shot LearningMachine Learning and Algorithms

Cited by 29

Learning Personal Representations from fMRI by Predicting Neurofeedback Performance

Osin, J., Wolf, L., Gurevitch, G., Keynan, J. N., Fruchtman-Steinbok, T., Or-Borichev, A., & Hendler, T. (2020) · Lecture Notes in Computer Science

EEG and Brain-Computer InterfacesFunctional Brain Connectivity Studies

Cited by 3

Execution Guided Line-by-Line Code Generation

Lavon, B., Katz, S., & Wolf, L. (2025) · arXiv

Software Engineering ResearchTeaching and Learning Programming

Cited by 1

Focus Your Attention (with Adaptive IIR Filters)

Lutati, S., Zimerman, I., & Wolf, L. (2023) · arXiv

Neural Networks and ApplicationsTopic Modeling

Cited by 0

VideoJAM: Joint Appearance-Motion Representations for Enhanced Motion Generation in Video Models

Chefer, H., Singer, U., Zohar, A., Kirstain, Y., Polyak, A., Taigman, Y., Wolf, L., & Sheynin, S. (2025) · arXiv

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 0