Isola, Phillip

Unpaired image-to-image translation using cycle-consistent adversarial networks

Zhu, J.-Y., Park, T., Isola, P., & Efros, A. A. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV)

Generative Adversarial Networks and Image SynthesisDomain Adaptation and Few-Shot Learning

Cited by 23,602

Image-to-Image Translation with Conditional Adversarial Networks

Isola, P., Zhu, J.-Y., Zhou, T., & Efros, A. A. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Generative Adversarial Networks and Image SynthesisDomain Adaptation and Few-Shot Learning

Cited by 22,930

The Unreasonable Effectiveness of Deep Features as a Perceptual Metric

Zhang, R., Isola, P., Efros, A. A., Shechtman, E., & Wang, O. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition

Image and Video Quality AssessmentGenerative Adversarial Networks and Image Synthesis

Cited by 14,623

Supervised Contrastive Learning

Khosla, P., Teterwak, P., Wang, C., Sarna, A., Tian, Y., Isola, P., Maschinot, A., Liu, C., & Krishnan, D. (2020) · arXiv

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 3,569

CyCADA: Cycle-Consistent Adversarial Domain Adaptation

Hoffman, J., Tzeng, E., Park, T., Zhu, J.-Y., Isola, P., Saenko, K., Efros, A. A., & Darrell, T. (2017) · arXiv

Domain Adaptation and Few-Shot LearningGenerative Adversarial Networks and Image Synthesis

Cited by 2,656

Contrastive Multiview Coding

Tian, Y., Krishnan, D., & Isola, P. (2020) · Lecture Notes in Computer Science

Multimodal Machine Learning ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 1,997

Rethinking Few-Shot Image Classification: A Good Embedding is All You Need?

Tian, Y., Wang, Y., Krishnan, D., Tenenbaum, J. B., & Isola, P. (2020) · Lecture Notes in Computer Science

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 952

Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere

Wang, T., & Isola, P. (2020) · arXiv

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 921

What makes for good views for contrastive learning

Tian, Y., Sun, C., Poole, B., Krishnan, D., Schmid, C., & Isola, P. (2020) · arXiv

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 773

Contrastive Multiview Coding

Tian, Y., Krishnan, D., & Isola, P. (2019) · arXiv

Domain Adaptation and Few-Shot LearningMultimodal Machine Learning Applications

Cited by 465

What Makes Fake Images Detectable? Understanding Properties that Generalize

Chai, L., Bau, D., Lim, S.-N., & Isola, P. (2020) · Lecture Notes in Computer Science

Digital Media Forensic DetectionGenerative Adversarial Networks and Image Synthesis

Cited by 357

Crisp Boundary Detection Using Pointwise Mutual Information

Isola, P., Zoran, D., Krishnan, D., & Adelson, E. H. (2014) · Lecture Notes in Computer Science

Advanced Neural Network ApplicationsMedical Image Segmentation Techniques

Cited by 199

Exploring Visual Prompts for Adapting Large-Scale Models

Bahng, H., Jahanian, A., Sankaranarayanan, S., & Isola, P. (2022) · arXiv

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 129

DreamSim: Learning New Dimensions of Human Visual Similarity using Synthetic Data

Fu, S., Tamir, N., Sundaram, S., Chai, L., Zhang, R., Dekel, T., & Isola, P. (2023) · Advances in Neural Information Processing Systems 36

Domain Adaptation and Few-Shot LearningGenerative Adversarial Networks and Image Synthesis

Cited by 108

DreamSim: Learning New Dimensions of Human Visual Similarity using Synthetic Data

Fu, S., Tamir, N., Sundaram, S., Chai, L., Zhang, R., Dekel, T., & Isola, P. (2023) · arXiv

Domain Adaptation and Few-Shot LearningGenerative Adversarial Networks and Image Synthesis

Cited by 108

Learning visual groups from co-occurrences in space and time

Isola, P., Zoran, D., Krishnan, D., & Adelson, E. H. (2015) · arXiv

Advanced Image and Video Retrieval TechniquesAdvanced Neural Network Applications

Cited by 90

Improving CLIP Training with Language Rewrites

Fan, L., Krishnan, D., Isola, P., Katabi, D., & Tian, Y. (2023) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 74

Scaling Laws of Synthetic Images for Model Training … for Now

Fan, L., Chen, K., Krishnan, D., Katabi, D., Isola, P., & Tian, Y. (2024) · 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Generative Adversarial Networks and Image SynthesisDomain Adaptation and Few-Shot Learning

Cited by 46

The Platonic Representation Hypothesis

Huh, M., Cheung, B., Wang, T., & Isola, P. (2024) · arXiv

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 35

Learning to Ground Multi-Agent Communication with Autoencoders

Lin, T., Huh, M., Stauffer, C., Lim, S.-N., & Isola, P. (2021) · arXiv

Multi-Agent Systems and NegotiationReinforcement Learning in Robotics

Cited by 26

A Vision Check-up for Language Models

Sharma, P., Shaham, T. R., Baradad, M., Rodriíuez-Muñoz, A., Duggal, S., Isola, P., Torralba, A., & Fu, S. (2024) · 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Multimodal Machine Learning ApplicationsGenerative Adversarial Networks and Image Synthesis

Cited by 15

Cycle Consistency as Reward: Learning Image-Text Alignment Without Human Preferences

Bahng, H., Chan, C., Durand, F., & Isola, P. (2025) · 2025 IEEE/CVF International Conference on Computer Vision (ICCV)

Multimodal Machine Learning ApplicationsGenerative Adversarial Networks and Image Synthesis

Cited by 3

Neural MMO 2.0: A Massively Multi-task Addition to Massively Multi-agent Learning

Suárez, J., Isola, P., Choe, K. W., Bloomin, D., Li, H. X., Pinnaparaju, N., Kanna, N., Scott, D., Sullivan, R., Shuman, R. S., et al. (2023) · arXiv

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 1

Neural MMO 2.0: A Massively Multi-task Addition to Massively Multi-agent Learning

Suarez, J., Bloomin, D., Choe, K. W., Li, H. X., Sullivan, R., Kanna, N., Scott, D., Shuman, R., Bradley, H., Castricato, L., et al. (2023) · Advances in Neural Information Processing Systems 36

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 1