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2020 – today
- 2023
[j5]Minyoung Huh, Hossein Mobahi, Richard Zhang, Brian Cheung, Pulkit Agrawal, Phillip Isola:
The Low-Rank Simplicity Bias in Deep Networks. Trans. Mach. Learn. Res. 2023 (2023)- [c64]Yangkun Chen, Joseph Suarez, Junjie Zhang, Chenghui Yu, Bo Wu, Hanmo Chen, Hengman Zhu, Rui Du, Shanliang Qian, Shuai Liu, Weijun Hong, Jinke He, Yibing Zhang, Liang Zhao, Clare Zhu, Julian Togelius, Sharada Mohanty, Jiaxin Chen, Xiu Li, Xiaolong Zhu, Phillip Isola:
Benchmarking Robustness and Generalization in Multi-Agent Systems: A Case Study on Neural MMO. AAMAS 2023: 2490-2492 - [c63]Lucy Chai, Richard Tucker, Zhengqi Li, Phillip Isola, Noah Snavely:
Persistent Nature: A Generative Model of Unbounded 3D Worlds. CVPR 2023: 20863-20874 - [c62]Kevin Frans, Phillip Isola:
Powderworld: A Platform for Understanding Generalization via Rich Task Distributions. ICLR 2023 - [c61]Jerry Ngo, Swami Sankaranarayanan, Phillip Isola:
Is CLIP Fooled by Optical Illusions? Tiny Papers @ ICLR 2023 - [c60]Minyoung Huh, Brian Cheung, Pulkit Agrawal, Phillip Isola:
Straightening Out the Straight-Through Estimator: Overcoming Optimization Challenges in Vector Quantized Networks. ICML 2023: 14096-14113 - [c59]Tongzhou Wang, Antonio Torralba, Phillip Isola, Amy Zhang:
Optimal Goal-Reaching Reinforcement Learning via Quasimetric Learning. ICML 2023: 36411-36430 - [i67]Sangnie Bhardwaj, Willie McClinton, Tongzhou Wang, Guillaume Lajoie, Chen Sun, Phillip Isola, Dilip Krishnan:
Steerable Equivariant Representation Learning. CoRR abs/2302.11349 (2023) - [i66]Lucy Chai, Richard Tucker, Zhengqi Li, Phillip Isola, Noah Snavely:
Persistent Nature: A Generative Model of Unbounded 3D Worlds. CoRR abs/2303.13515 (2023) - [i65]Tongzhou Wang, Antonio Torralba, Phillip Isola, Amy Zhang:
Optimal Goal-Reaching Reinforcement Learning via Quasimetric Learning. CoRR abs/2304.01203 (2023) - [i64]Minyoung Huh, Brian Cheung, Pulkit Agrawal, Phillip Isola:
Straightening Out the Straight-Through Estimator: Overcoming Optimization Challenges in Vector Quantized Networks. CoRR abs/2305.08842 (2023) - [i63]Lijie Fan, Dilip Krishnan, Phillip Isola, Dina Katabi, Yonglong Tian:
Improving CLIP Training with Language Rewrites. CoRR abs/2305.20088 (2023) - [i62]Yonglong Tian, Lijie Fan, Phillip Isola, Huiwen Chang, Dilip Krishnan:
StableRep: Synthetic Images from Text-to-Image Models Make Strong Visual Representation Learners. CoRR abs/2306.00984 (2023) - [i61]Miriam Cha, Gregory Angelides, Mark Hamilton, Andy Soszynski, Brandon Swenson, Nathaniel Maidel, Phillip Isola, Taylor Perron, Bill Freeman:
MultiEarth 2023 - Multimodal Learning for Earth and Environment Workshop and Challenge. CoRR abs/2306.04738 (2023) - [i60]Stephanie Fu, Netanel Tamir, Shobhita Sundaram, Lucy Chai, Richard Zhang, Tali Dekel, Phillip Isola:
DreamSim: Learning New Dimensions of Human Visual Similarity using Synthetic Data. CoRR abs/2306.09344 (2023) - [i59]William Shen, Ge Yang, Alan Yu, Jansen Wong, Leslie Pack Kaelbling, Phillip Isola:
Distilled Feature Fields Enable Few-Shot Language-Guided Manipulation. CoRR abs/2308.07931 (2023) - [i58]Yangkun Chen, Joseph Suarez, Junjie Zhang, Chenghui Yu, Bo Wu, Hanmo Chen, Hengman Zhu, Rui Du, Shanliang Qian, Shuai Liu, Weijun Hong, Jinke He, Yibing Zhang, Liang Zhao, Clare Zhu, Julian Togelius, Sharada Mohanty, Jiaxin Chen, Xiu Li, Xiaolong Zhu, Phillip Isola:
Benchmarking Robustness and Generalization in Multi-Agent Systems: A Case Study on Neural MMO. CoRR abs/2308.15802 (2023) - 2022
- [c58]Yen-Chen Lin, Pete Florence, Andy Zeng, Jonathan T. Barron, Yilun Du, Wei-Chiu Ma, Anthony Simeonov, Alberto Rodriguez Garcia, Phillip Isola:
MIRA: Mental Imagery for Robotic Affordances. CoRL 2022: 1916-1927 - [c57]Caroline Chan, Frédo Durand, Phillip Isola:
Learning to generate line drawings that convey geometry and semantics. CVPR 2022: 7905-7915 - [c56]Jingwei Ma, Lucy Chai, Minyoung Huh, Tongzhou Wang, Ser-Nam Lim, Phillip Isola, Antonio Torralba:
Totems: Physical Objects for Verifying Visual Integrity. ECCV (14) 2022: 164-180 - [c55]Lucy Chai, Michaël Gharbi, Eli Shechtman, Phillip Isola, Richard Zhang:
Any-Resolution Training for High-Resolution Image Synthesis. ECCV (16) 2022: 170-188 - [c54]Tongzhou Wang, Phillip Isola:
On the Learning and Learnability of Quasimetrics. ICLR 2022 - [c53]Ali Jahanian, Xavier Puig, Yonglong Tian, Phillip Isola:
Generative Models as a Data Source for Multiview Representation Learning. ICLR 2022 - [c52]Tongzhou Wang, Simon S. Du, Antonio Torralba, Phillip Isola, Amy Zhang, Yuandong Tian:
Denoised MDPs: Learning World Models Better Than the World Itself. ICML 2022: 22591-22612 - [c51]Yen-Chen Lin, Pete Florence, Jonathan T. Barron, Tsung-Yi Lin, Alberto Rodriguez, Phillip Isola:
NeRF-Supervision: Learning Dense Object Descriptors from Neural Radiance Fields. ICRA 2022: 6496-6503 - [c50]Chuang Gan, Xiaoyu Chen, Phillip Isola, Antonio Torralba, Joshua B. Tenenbaum:
Noisy Agents: Self-supervised Exploration by Predicting Auditory Events. IROS 2022: 9259-9265 - [c49]Manel Baradad, Chun-Fu Richard Chen, Jonas Wulff, Tongzhou Wang, Rogério Feris, Antonio Torralba, Phillip Isola:
Procedural Image Programs for Representation Learning. NeurIPS 2022 - [c48]Swami Sankaranarayanan, Anastasios Angelopoulos, Stephen Bates, Yaniv Romano, Phillip Isola:
Semantic uncertainty intervals for disentangled latent spaces. NeurIPS 2022 - [c47]Wei-Cheng Tseng, Tsun-Hsuan Johnson Wang, Yen-Chen Lin, Phillip Isola:
Offline Multi-Agent Reinforcement Learning with Knowledge Distillation. NeurIPS 2022 - [i57]Yen-Chen Lin, Pete Florence, Jonathan T. Barron, Tsung-Yi Lin, Alberto Rodriguez Garcia, Phillip Isola:
NeRF-Supervision: Learning Dense Object Descriptors from Neural Radiance Fields. CoRR abs/2203.01913 (2022) - [i56]Caroline Chan, Frédo Durand, Phillip Isola:
Learning to generate line drawings that convey geometry and semantics. CoRR abs/2203.12691 (2022) - [i55]Hyojin Bahng, Ali Jahanian, Swami Sankaranarayanan, Phillip Isola:
Visual Prompting: Modifying Pixel Space to Adapt Pre-trained Models. CoRR abs/2203.17274 (2022) - [i54]Lucy Chai, Michaël Gharbi, Eli Shechtman, Phillip Isola, Richard Zhang:
Any-resolution Training for High-resolution Image Synthesis. CoRR abs/2204.07156 (2022) - [i53]Miriam Cha, Kuan Wei Huang, Morgan Schmidt, Gregory Angelides, Mark Hamilton, Sam Goldberg, Armando Cabrera, Phillip Isola, Taylor Perron, Bill Freeman, Yen-Chen Lin, Brandon Swenson, Jean E. Piou:
MultiEarth 2022 - Multimodal Learning for Earth and Environment Workshop and Challenge. CoRR abs/2204.07649 (2022) - [i52]Tongzhou Wang, Simon S. Du, Antonio Torralba, Phillip Isola, Amy Zhang, Yuandong Tian:
Denoised MDPs: Learning World Models Better Than the World Itself. CoRR abs/2206.15477 (2022) - [i51]Tongzhou Wang, Phillip Isola:
On the Learning and Learnablity of Quasimetrics. CoRR abs/2206.15478 (2022) - [i50]Vijay Gadepally, Gregory Angelides, Andrei Barbu, Andrew Bowne, Laura J. Brattain, Tamara Broderick, Armando Cabrera, Glenn Carl, Ronisha Carter, Miriam Cha, Emilie Cowen, Jesse Cummings, Bill Freeman, James R. Glass, Sam Goldberg, Mark Hamilton, Thomas Heldt, Kuan Wei Huang, Phillip Isola, Boris Katz, Jamie Koerner, Yen-Chen Lin, David Mayo, Kyle McAlpin, Taylor Perron, Jean E. Piou, Hrishikesh M. Rao, Hayley Reynolds, Kaira Samuel, Siddharth Samsi, Morgan Schmidt, Leslie Shing, Olga Simek, Brandon Swenson, Vivienne Sze, Jonathan Taylor, Paul Tylkin, Mark Veillette, Matthew L. Weiss, Allan B. Wollaber, Sophia Yuditskaya, Jeremy Kepner:
Developing a Series of AI Challenges for the United States Department of the Air Force. CoRR abs/2207.07033 (2022) - [i49]Swami Sankaranarayanan, Anastasios N. Angelopoulos, Stephen Bates, Yaniv Romano, Phillip Isola:
Semantic uncertainty intervals for disentangled latent spaces. CoRR abs/2207.10074 (2022) - [i48]Jingwei Ma, Lucy Chai, Minyoung Huh, Tongzhou Wang, Ser-Nam Lim, Phillip Isola, Antonio Torralba:
Totems: Physical Objects for Verifying Visual Integrity. CoRR abs/2209.13032 (2022) - [i47]Kevin Frans, Phillip Isola:
Powderworld: A Platform for Understanding Generalization via Rich Task Distributions. CoRR abs/2211.13051 (2022) - [i46]Tongzhou Wang, Phillip Isola:
Improved Representation of Asymmetrical Distances with Interval Quasimetric Embeddings. CoRR abs/2211.15120 (2022) - [i45]Manel Baradad, Chun-Fu Chen, Jonas Wulff, Tongzhou Wang, Rogério Feris, Antonio Torralba, Phillip Isola:
Procedural Image Programs for Representation Learning. CoRR abs/2211.16412 (2022) - [i44]Yen-Chen Lin, Pete Florence, Andy Zeng, Jonathan T. Barron, Yilun Du, Wei-Chiu Ma, Anthony Simeonov, Alberto Rodriguez Garcia, Phillip Isola:
MIRA: Mental Imagery for Robotic Affordances. CoRR abs/2212.06088 (2022) - 2021
- [c46]Lucy Chai, Jun-Yan Zhu, Eli Shechtman, Phillip Isola, Richard Zhang:
Ensembling With Deep Generative Views. CVPR 2021: 14997-15007 - [c45]Oran Lang, Yossi Gandelsman, Michal Yarom, Yoav Wald, Gal Elidan, Avinatan Hassidim, William T. Freeman, Phillip Isola, Amir Globerson, Michal Irani, Inbar Mosseri:
Explaining in Style: Training a GAN to explain a classifier in StyleSpace. ICCV 2021: 673-682 - [c44]Yilun Du, Chuang Gan, Phillip Isola:
Curious Representation Learning for Embodied Intelligence. ICCV 2021: 10388-10397 - [c43]Alex Andonian, Taesung Park, Bryan Russell, Phillip Isola, Jun-Yan Zhu, Richard Zhang:
Contrastive Feature Loss for Image Prediction. ICCVW 2021: 1934-1943 - [c42]Lucy Chai, Jonas Wulff, Phillip Isola:
Using latent space regression to analyze and leverage compositionality in GANs. ICLR 2021 - [c41]Yen-Chen Lin, Pete Florence, Jonathan T. Barron, Alberto Rodriguez, Phillip Isola, Tsung-Yi Lin:
iNeRF: Inverting Neural Radiance Fields for Pose Estimation. IROS 2021: 1323-1330 - [c40]Chuang Gan, Abhishek Bhandwaldar, Antonio Torralba, Joshua B. Tenenbaum, Phillip Isola:
OPEn: An Open-ended Physics Environment for Learning Without a Task. IROS 2021: 5878-5885 - [c39]Manel Baradad Jurjo, Jonas Wulff, Tongzhou Wang, Phillip Isola, Antonio Torralba:
Learning to See by Looking at Noise. NeurIPS 2021: 2556-2569 - [c38]Kenneth Derek, Phillip Isola:
Adaptable Agent Populations via a Generative Model of Policies. NeurIPS 2021: 3902-3913 - [c37]Toru Lin, Jacob Huh, Christopher Stauffer, Ser-Nam Lim, Phillip Isola:
Learning to Ground Multi-Agent Communication with Autoencoders. NeurIPS 2021: 15230-15242 - [c36]Joseph Suarez, Yilun Du, Clare Zhu, Igor Mordatch, Phillip Isola:
The Neural MMO Platform for Massively Multiagent Research. NeurIPS Datasets and Benchmarks 2021 - [i43]Lucy Chai, Jonas Wulff, Phillip Isola:
Using latent space regression to analyze and leverage compositionality in GANs. CoRR abs/2103.10426 (2021) - [i42]Minyoung Huh, Hossein Mobahi, Richard Zhang, Brian Cheung, Pulkit Agrawal, Phillip Isola:
The Low-Rank Simplicity Bias in Deep Networks. CoRR abs/2103.10427 (2021) - [i41]Oran Lang, Yossi Gandelsman, Michal Yarom, Yoav Wald, Gal Elidan, Avinatan Hassidim, William T. Freeman, Phillip Isola, Amir Globerson, Michal Irani, Inbar Mosseri:
Explaining in Style: Training a GAN to explain a classifier in StyleSpace. CoRR abs/2104.13369 (2021) - [i40]Lucy Chai, Jun-Yan Zhu, Eli Shechtman, Phillip Isola, Richard Zhang:
Ensembling with Deep Generative Views. CoRR abs/2104.14551 (2021) - [i39]Yilun Du, Chuang Gan, Phillip Isola:
Curious Representation Learning for Embodied Intelligence. CoRR abs/2105.01060 (2021) - [i38]Ali Jahanian, Xavier Puig, Yonglong Tian, Phillip Isola:
Generative Models as a Data Source for Multiview Representation Learning. CoRR abs/2106.05258 (2021) - [i37]Manel Baradad, Jonas Wulff, Tongzhou Wang, Phillip Isola, Antonio Torralba:
Learning to See by Looking at Noise. CoRR abs/2106.05963 (2021) - [i36]Yen-Chen Lin, Andy Zeng, Shuran Song, Phillip Isola, Tsung-Yi Lin:
Learning to See before Learning to Act: Visual Pre-training for Manipulation. CoRR abs/2107.00646 (2021) - [i35]Kenneth Derek, Phillip Isola:
Adaptable Agent Populations via a Generative Model of Policies. CoRR abs/2107.07506 (2021) - [i34]Chuang Gan, Abhishek Bhandwaldar, Antonio Torralba, Joshua B. Tenenbaum, Phillip Isola:
OPEn: An Open-ended Physics Environment for Learning Without a Task. CoRR abs/2110.06912 (2021) - [i33]Joseph Suarez, Yilun Du, Clare Zhu, Igor Mordatch, Phillip Isola:
The Neural MMO Platform for Massively Multiagent Research. CoRR abs/2110.07594 (2021) - [i32]Toru Lin, Minyoung Huh, Christopher Stauffer, Ser-Nam Lim, Phillip Isola:
Learning to Ground Multi-Agent Communication with Autoencoders. CoRR abs/2110.15349 (2021) - [i31]Alex Andonian, Taesung Park, Bryan Russell, Phillip Isola, Jun-Yan Zhu, Richard Zhang:
Contrastive Feature Loss for Image Prediction. CoRR abs/2111.06934 (2021) - 2020
- [c35]Joseph Suarez, Yilun Du, Igor Mordatch, Phillip Isola:
Neural MMO v1.3: A Massively Multiagent Game Environment for Training and Evaluating Neural Networks. AAMAS 2020: 2020-2022 - [c34]Lucy Chai, David Bau
, Ser-Nam Lim, Phillip Isola:
What Makes Fake Images Detectable? Understanding Properties that Generalize. ECCV (26) 2020: 103-120 - [c33]Yonglong Tian, Yue Wang, Dilip Krishnan, Joshua B. Tenenbaum, Phillip Isola:
Rethinking Few-Shot Image Classification: A Good Embedding is All You Need? ECCV (14) 2020: 266-282 - [c32]Yonglong Tian, Dilip Krishnan, Phillip Isola:
Contrastive Multiview Coding. ECCV (11) 2020: 776-794 - [c31]Ali Jahanian, Lucy Chai, Phillip Isola:
On the "steerability" of generative adversarial networks. ICLR 2020 - [c30]Yonglong Tian, Dilip Krishnan, Phillip Isola:
Contrastive Representation Distillation. ICLR 2020 - [c29]Tongzhou Wang, Phillip Isola:
Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere. ICML 2020: 9929-9939 - [c28]Yen-Chen Lin, Andy Zeng, Shuran Song, Phillip Isola, Tsung-Yi Lin:
Learning to See before Learning to Act: Visual Pre-training for Manipulation. ICRA 2020: 7286-7293 - [c27]Prannay Khosla, Piotr Teterwak, Chen Wang, Aaron Sarna, Yonglong Tian, Phillip Isola, Aaron Maschinot, Ce Liu, Dilip Krishnan:
Supervised Contrastive Learning. NeurIPS 2020 - [c26]Yonglong Tian, Chen Sun, Ben Poole, Dilip Krishnan, Cordelia Schmid, Phillip Isola:
What Makes for Good Views for Contrastive Learning? NeurIPS 2020 - [i30]Joseph Suarez, Yilun Du, Igor Mordatch, Phillip Isola:
Neural MMO v1.3: A Massively Multiagent Game Environment for Training and Evaluating Neural Networks. CoRR abs/2001.12004 (2020) - [i29]Yonglong Tian, Yue Wang, Dilip Krishnan, Joshua B. Tenenbaum, Phillip Isola:
Rethinking Few-Shot Image Classification: a Good Embedding Is All You Need? CoRR abs/2003.11539 (2020) - [i28]Prannay Khosla, Piotr Teterwak, Chen Wang, Aaron Sarna, Yonglong Tian, Phillip Isola, Aaron Maschinot, Ce Liu, Dilip Krishnan:
Supervised Contrastive Learning. CoRR abs/2004.11362 (2020) - [i27]Tongzhou Wang, Phillip Isola:
Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere. CoRR abs/2005.10242 (2020) - [i26]Yonglong Tian, Chen Sun, Ben Poole, Dilip Krishnan, Cordelia Schmid, Phillip Isola:
What makes for good views for contrastive learning. CoRR abs/2005.10243 (2020) - [i25]Chuang Gan, Xiaoyu Chen, Phillip Isola, Antonio Torralba, Joshua B. Tenenbaum:
Noisy Agents: Self-supervised Exploration by Predicting Auditory Events. CoRR abs/2007.13729 (2020) - [i24]Lucy Chai, David Bau, Ser-Nam Lim, Phillip Isola:
What makes fake images detectable? Understanding properties that generalize. CoRR abs/2008.10588 (2020) - [i23]Yen-Chen Lin, Pete Florence, Jonathan T. Barron, Alberto Rodriguez Garcia, Phillip Isola, Tsung-Yi Lin:
iNeRF: Inverting Neural Radiance Fields for Pose Estimation. CoRR abs/2012.05877 (2020)
2010 – 2019
- 2019
- [c25]Yen-Chen Lin, Maria Bauzá, Phillip Isola:
Experience-Embedded Visual Foresight. CoRL 2019: 1015-1024 - [c24]Assaf Shocher, Shai Bagon, Phillip Isola, Michal Irani:
InGAN: Capturing and Retargeting the "DNA" of a Natural Image. ICCV 2019: 4491-4500 - [c23]Lore Goetschalckx, Alex Andonian, Aude Oliva, Phillip Isola:
GANalyze: Toward Visual Definitions of Cognitive Image Properties. ICCV 2019: 5743-5752 - [c22]Maria Bauzá, Ferran Alet, Yen-Chen Lin, Tomás Lozano-Pérez, Leslie Pack Kaelbling, Phillip Isola, Alberto Rodriguez:
Omnipush: accurate, diverse, real-world dataset of pushing dynamics with RGB-D video. IROS 2019: 4265-4272 - [c21]Deepak Pathak, Christopher Lu, Trevor Darrell, Phillip Isola, Alexei A. Efros:
Learning to Control Self-Assembling Morphologies: A Study of Generalization via Modularity. NeurIPS 2019: 2292-2302 - [i22]Deepak Pathak, Christopher Lu, Trevor Darrell, Phillip Isola, Alexei A. Efros:
Learning to Control Self-Assembling Morphologies: A Study of Generalization via Modularity. CoRR abs/1902.05546 (2019) - [i21]Joseph Suarez, Yilun Du, Phillip Isola, Igor Mordatch:
Neural MMO: A Massively Multiagent Game Environment for Training and Evaluating Intelligent Agents. CoRR abs/1903.00784 (2019) - [i20]Yonglong Tian, Dilip Krishnan, Phillip Isola:
Contrastive Multiview Coding. CoRR abs/1906.05849 (2019) - [i19]Lore Goetschalckx, Alex Andonian, Aude Oliva, Phillip Isola:
Lore Goetschalckx, Alex Andonian, Aude Oliva, Phillip Isola: GANalyze: Toward Visual Definitions of Cognitive Image Properties. CoRR abs/1906.10112 (2019) - [i18]Ali Jahanian, Lucy Chai, Phillip Isola:
On the "steerability" of generative adversarial networks. CoRR abs/1907.07171 (2019) - [i17]Maria Bauzá, Ferran Alet, Yen-Chen Lin, Tomás Lozano-Pérez, Leslie Pack Kaelbling, Phillip Isola, Alberto Rodriguez:
Omnipush: accurate, diverse, real-world dataset of pushing dynamics with RGB-D video. CoRR abs/1910.00618 (2019) - [i16]Yonglong Tian, Dilip Krishnan, Phillip Isola:
Contrastive Representation Distillation. CoRR abs/1910.10699 (2019) - [i15]Yen-Chen Lin, Maria Bauzá, Phillip Isola:
Experience-Embedded Visual Foresight. CoRR abs/1911.05071 (2019) - 2018
- [j4]Johanna Delanoy, Mathieu Aubry, Phillip Isola, Alexei A. Efros, Adrien Bousseau:
3D Sketching using Multi-View Deep Volumetric Prediction. Proc. ACM Comput. Graph. Interact. Tech. 1(1): 21:1-21:22 (2018) - [c20]Richard Zhang, Phillip Isola, Alexei A. Efros, Eli Shechtman, Oliver Wang:
The Unreasonable Effectiveness of Deep Features as a Perceptual Metric. CVPR 2018: 586-595 - [c19]Judy Hoffman, Eric Tzeng, Taesung Park, Jun-Yan Zhu, Phillip Isola, Kate Saenko, Alexei A. Efros, Trevor Darrell:
CyCADA: Cycle-Consistent Adversarial Domain Adaptation. ICML 2018: 1994-2003 - [c18]Rein Houthooft, Yuhua Chen, Phillip Isola, Bradly C. Stadie, Filip Wolski, Jonathan Ho, Pieter Abbeel:
Evolved Policy Gradients. NeurIPS 2018: 5405-5414 - [i14]Richard Zhang, Phillip Isola, Alexei A. Efros, Eli Shechtman, Oliver Wang:
The Unreasonable Effectiveness of Deep Features as a Perceptual Metric. CoRR abs/1801.03924 (2018) - [i13]Rein Houthooft, Richard Y. Chen, Phillip Isola, Bradly C. Stadie, Filip Wolski, Jonathan Ho, Pieter Abbeel:
Evolved Policy Gradients. CoRR abs/1802.04821 (2018) - [i12]Assaf Shocher, Shai Bagon, Phillip Isola, Michal Irani:
Internal Distribution Matching for Natural Image Retargeting. CoRR abs/1812.00231 (2018) - 2017
- [j3]Richard Zhang, Jun-Yan Zhu, Phillip Isola, Xinyang Geng, Angela S. Lin, Tianhe Yu, Alexei A. Efros:
Real-time user-guided image colorization with learned deep priors. ACM Trans. Graph. 36(4): 119:1-119:11 (2017) - [c17]Ali Jahanian, Phillip Isola, Donglai Wei:
Mining Visual Evolution in 21 Years of Web Design. CHI Extended Abstracts 2017: 2676-2682 - [c16]Richard Zhang, Phillip Isola, Alexei A. Efros:
Split-Brain Autoencoders: Unsupervised Learning by Cross-Channel Prediction. CVPR 2017: 645-654 - [c15]Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, Alexei A. Efros:
Image-to-Image Translation with Conditional Adversarial Networks. CVPR 2017: 5967-5976 - [c14]Jun-Yan Zhu, Taesung Park, Phillip Isola, Alexei A. Efros:
Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks. ICCV 2017: 2242-2251 - [c13]Ashvin Nair, Dian Chen, Pulkit Agrawal, Phillip Isola, Pieter Abbeel, Jitendra Malik, Sergey Levine:
Combining self-supervised learning and imitation for vision-based rope manipulation. ICRA 2017: 2146-2153 - [i11]Ashvin Nair, Dian Chen, Pulkit Agrawal, Phillip Isola, Pieter Abbeel, Jitendra Malik, Sergey Levine:
Combining Self-Supervised Learning and Imitation for Vision-Based Rope Manipulation. CoRR abs/1703.02018 (2017) - [i10]Jun-Yan Zhu, Taesung Park, Phillip Isola, Alexei A. Efros:
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks. CoRR abs/1703.10593 (2017) - [i9]Richard Zhang, Jun-Yan Zhu, Phillip Isola, Xinyang Geng, Angela S. Lin, Tianhe Yu, Alexei A. Efros:
Real-Time User-Guided Image Colorization with Learned Deep Priors. CoRR abs/1705.02999 (2017) - [i8]Johanna Delanoy, Adrien Bousseau, Mathieu Aubry, Phillip Isola, Alexei A. Efros:
What You Sketch Is What You Get: 3D Sketching using Multi-View Deep Volumetric Prediction. CoRR abs/1707.08390 (2017) - [i7]Judy Hoffman, Eric Tzeng, Taesung Park, Jun-Yan Zhu, Phillip Isola, Kate Saenko, Alexei A. Efros, Trevor Darrell:
CyCADA: Cycle-Consistent Adversarial Domain Adaptation. CoRR abs/1711.03213 (2017) - 2016
- [c12]Andrew Owens, Phillip Isola, Josh H. McDermott, Antonio Torralba, Edward H. Adelson, William T. Freeman:
Visually Indicated Sounds. CVPR 2016: 2405-2413 - [c11]