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Phillip Isola

Phillip Isola

D-Index & Metrics

Computer Science

D-Index
48
Citations
75735
World Ranking
5987
National Ranking
2693

Overview

Phillip Isola is affiliated with the Massachusetts Institute of Technology (MIT) in the United States. Their research primarily focuses on computer science, with a significant contribution to subfields such as computer vision and pattern recognition, artificial intelligence, aerospace engineering, biophysics, and cognitive neuroscience.

The scientist has published extensively, with a total of 162 publications in computer science and 88 specifically in computer vision and pattern recognition. Their work is also notable in areas including artificial intelligence and emerging interdisciplinary fields.

Phillip Isola's recent publications include the following:

  • What Makes for Good Views for Contrastive Learning?, 2020, arXiv (Cornell University)
  • Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere, 2020, arXiv (Cornell University)
  • iNeRF: Inverting Neural Radiance Fields for Pose Estimation, 2021, 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
  • Supervised Contrastive Learning, 2020, arXiv (Cornell University)

Their frequent publication venues include:

  • arXiv (Cornell University)
  • 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • 2022 International Conference on Robotics and Automation (ICRA)
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Phillip Isola collaborates frequently with several co-authors, including Tongzhou Wang, Lucy Chai, Antonio Torralba, Yonglong Tian, and Dilip Krishnan. These collaborations span a variety of topics and venues.

The scientist's main research topics encompass:

  • Domain Adaptation and Few-Shot Learning
  • Multimodal Machine Learning Applications
  • Generative Adversarial Networks and Image Synthesis
  • Advanced Image and Video Retrieval Techniques
  • Reinforcement Learning in Robotics
  • Advanced Vision and Imaging
  • Advanced Neural Network Applications

Best Publications

  • Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks

    Jun-Yan Zhu;Taesung Park;Phillip Isola;Alexei A. Efros

  • Image-to-Image Translation with Conditional Adversarial Networks

    Phillip Isola;Jun-Yan Zhu;Tinghui Zhou;Alexei A. Efros

  • The Unreasonable Effectiveness of Deep Features as a Perceptual Metric

    Richard Zhang;Phillip Isola;Phillip Isola;Alexei A. Efros;Eli Shechtman

  • Colorful Image Colorization

    Richard Yi Zhang;Phillip Isola;Alexei A. Efros

  • CyCADA: Cycle-Consistent Adversarial Domain Adaptation

    Judy Hoffman;Eric Tzeng;Taesung Park;Jun-Yan Zhu

  • Contrastive Multiview Coding

    Yonglong Tian;Dilip Krishnan;Phillip Isola

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

    Yonglong Tian;Yue Wang;Dilip Krishnan;Joshua B. Tenenbaum

  • What Makes a Visualization Memorable

    Michelle A. Borkin;Azalea A. Vo;Zoya Bylinskii;Phillip Isola

  • What Makes for Good Views for Contrastive Learning

    Yonglong Tian;Chen Sun;Ben Poole;Dilip Krishnan

  • Split-Brain Autoencoders: Unsupervised Learning by Cross-Channel Prediction

    Richard Zhang;Phillip Isola;Alexei A. Efros

  • Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere

    Tongzhou Wang;Phillip Isola

  • Real-time user-guided image colorization with learned deep priors

    Richard Zhang;Jun-Yan Zhu;Phillip Isola;Xinyang Geng

  • Contrastive Representation Distillation

    Yonglong Tian;Dilip Krishnan;Phillip Isola

  • What makes an image memorable

    Phillip Isola;Jianxiong Xiao;Antonio Torralba;Aude Oliva

  • Supervised Contrastive Learning

    Prannay Khosla;Piotr Teterwak;Chen Wang;Aaron Sarna

  • What Makes a Photograph Memorable

    Phillip Isola;Jianxiong Xiao;Devi Parikh;Antonio Torralba

  • Visually Indicated Sounds

    Andrew Owens;Phillip Isola;Josh McDermott;Antonio Torralba

  • iNeRF: Inverting Neural Radiance Fields for Pose Estimation

    Lin Yen-Chen;Pete Florence;Jonathan T. Barron;Alberto Rodriguez

  • What Makes Fake Images Detectable? Understanding Properties that Generalize

    Lucy Chai;David Bau;Ser-Nam Lim;Phillip Isola

  • Intrinsic and extrinsic effects on image memorability

    Zoya Bylinskii;Phillip Isola;Constance Bainbridge;Antonio Torralba

  • Combining self-supervised learning and imitation for vision-based rope manipulation

    Ashvin Nair;Dian Chen;Pulkit Agrawal;Phillip Isola

  • GANalyze: Toward visual definitions of cognitive image properties

    Lore Goetschalckx;Lore Goetschalckx;Alex Andonian;Aude Oliva;Phillip Isola

Frequent Co-Authors

Alexei A. Efros
Alexei A. Efros University of California, Berkeley
Dilip Krishnan
Dilip Krishnan Google (United States)
Jun-Yan Zhu
Jun-Yan Zhu Carnegie Mellon University
Igor Mordatch
Igor Mordatch Google (United States)
Michal Irani
Michal Irani Weizmann Institute of Science
Chuang Gan
Chuang Gan University of Massachusetts Amherst

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