Carlos Esteves

I am a Research Scientist at Google Research, NYC. I completed my Ph.D. in Computer and Information Science at the GRASP Laboratory, University of Pennsylvania, under the supervision of Kostas Daniilidis. Prior to that I received the B.S. in computer engineering and M.S. in electronic and computer engineering degrees from the Aeronautics Institute of Technology (ITA) in Brazil.

• Jul 14, 2023: LU-NeRF and ASIC have been accepted to ICCV'23!
• Jun 8, 2023: Scaling Spherical CNNs has been accepted to ICML'23!
• Sep 21, 2022: Check out this Google AI Blog post about our recent progress in novel view synthesis.
• Jul 26, 2022: Generalizable Patch-Based Neural Rendering has been accepted to ECCV'22! See the project page for code and more details!
• Jun 23, 2022: Light Field Neural Rendering is among the 33 best paper finalists (out of 8,161 submissions) at CVPR'22! See the project page for all details!
• Jul 19, 2021: Implicit-PDF: Non-Parametric Representation of Probability Distributions on the Rotation Manifold has been accepted to ICML and will be presented this week! See the project page for all details!
• Sep 26, 2020: Spin-Weighted Spherical CNNs has been accepted to NeurIPS! Camera-ready here, code coming soon!
• Apr 13, 2020: I wrote a manuscript about the theory behind Group CNNs, "Theoretical Aspects of Group Equivariant Neural Networks". Check it out here.
• Sep 09, 2019: The extended version of our paper Learning SO(3) Equivariant Representations with Spherical CNNs will appear on IJCV "Best of ECCV 2018" special edition. New version is already available here.
• Jul 22, 2019: Equivariant Multi-View Networks has been accepted as oral to ICCV 2019! Acceptance rate was 4.6%. Paper here.
• Apr 23, 2019: Cross-domain 3D Equivariant Image Embeddings has been accepted to ICML! Camera-ready available here.
• Jul 05, 2018: Learning SO(3) Equivariant Representations with Spherical CNNs has been accepted as an oral presentation to ECCV 2018! Acceptance rate was 2.4%. Camera-ready version here.
• Jan 31, 2018: Polar Transformer Networks has been accepted at ICLR 2018, with top 3% review scores!

My research is on computer vision and machine learning. I'm interested in 3D vision, pose estimation, equivariant representations, and machine learning for science.

Scaling Spherical CNNs
Carlos Esteves, Jean-Jacques Slotine, Ameesh Makadia
International Conference on Machine Learning, ICML 2023.
[ pdf | code ]

LU-NeRF: Scene and Pose Estimation by Synchronizing Local Unposed NeRFs
Zezhou Cheng, Carlos Esteves, Varun Jampani, Abhishek Kar, Subhransu Maji, Ameesh Makadia
International Conference on Computer Vision, ICCV 2023.
[ pdf | project page ]

Light Field Neural Rendering
Mohammed Suhail, Carlos Esteves, Leonid Sigal, Ameesh Makadia
Conference on Computer Vision and Pattern Recognition, CVPR 2022 (oral and best paper finalist; top 0.4%).
[ pdf | code | project page ]

Generalizable Patch-Based Neural Rendering
Mohammed Suhail, Carlos Esteves, Leonid Sigal, Ameesh Makadia
European Conference on Computer Vision, ECCV 2022 (oral; acceptance rate 2.7%).
[ pdf | code | project page ]

Implicit-PDF: Non-Parametric Representation of Probability Distributions on the Rotation Manifold
Kieran Murphy, Carlos Esteves, Varun Jampani, Srikumar Ramalingam, Ameesh Makadia
International Conference on Machine Learning, ICML 2021.
[ pdf | code | project page ]

Spin-Weighted Spherical CNNs
Carlos Esteves, Ameesh Makadia, Kostas Daniilidis.
Conference on Neural Information Processing Systems, NeurIPS 2020.
[ pdf | code | talk ]

Equivariant Multi-View Networks
Carlos Esteves, Yinshuang Xu, Christine Allen-Blanchette, Kostas Daniilidis.
International Conference on Computer Vision, ICCV 2019 (oral; acceptance rate 4.6%).
[ pdf | poster | talk | code ]

Cross-domain 3D Equivariant Image Embeddings
Carlos Esteves, Avneesh Sud, Zhengyi Luo, Kostas Daniilidis, Ameesh Makadia.
International Conference on Machine Learning, ICML 2019.
[ pdf | poster ]

Learning SO(3) Equivariant Representations with Spherical CNNs
Carlos Esteves, Christine Allen-Blanchette, Ameesh Makadia, Kostas Daniilidis.
European Conference on Computer Vision, ECCV 2018 (oral; acceptance rate 2.4%).
International Journal of Computer Vision, "Best of ECCV 2018" special edition, (IJCV 2019).
[ pdf | poster | talk | code | IJCV extended version ]

Labeling Panoramas with Spherical Hourglass Networks
Carlos Esteves, Kostas Daniilidis, Ameesh Makadia.
360° Perception and Interaction Workshop at ECCV 2018.
[ pdf | poster ]

Polar Transformer Networks
Carlos Esteves, Christine Allen-Blanchette, Xiaowei Zhou, Kostas Daniilidis.
International Conference on Learning Representations, ICLR 2018.
[ pdf | poster | code | OpenReview ]

An Analysis of SVD for Deep Rotation Estimation
Jake Levinson, Carlos Esteves, Kefan Chen, Noah Snavely, Angjoo Kanazawa, Afshin Rostamizadeh, Ameesh Makadia
Conference on Neural Information Processing Systems, NeurIPS 2020.
[ pdf ]

Learning Equivariant Representations
Carlos Esteves
Ph.D. Thesis
[ pdf ]

Theoretical Aspects of Group Equivariant Neural Networks
Carlos Esteves
[ pdf ]

• CVPR reviewer (IEEE/CVF Conference on Computer Vision and Pattern Recognition)
  • CVPR 2019 Outstanding Reviewer
  • CVPR 2021 Outstanding Reviewer
  • CVPR 2022 Outstanding Reviewer (top 2.4%)
• ICLR Reviewer (International Conference on Learning Representations)
  • ICLR 2022 Highlighted Reviewer (top 8.8%)
• ICML reviewer (International Conference on Machine Learning)
  • ICML 2021 Expert Reviewer
• NeurIPS reviewer (Conference on Neural Information Processing Systems)
• ICCV reviewer (IEEE International Conference on Computer Vision)
• ECCV reviewer (European Conference on Computer Vison)
• IJCV reviewer (International Journal of Computer Vision)
• TPAMI reviewer (IEEE Transactions on Pattern Analysis and Machine Intelligence)
• JMLR reviewer (Journal of Machine Learning Research)
• AAAI reviewer (AAAI Conference on Artificial Intelligence)
• GMDL reviewer (Geometry Meets Deep Learning Workshop)
• 360PI reviewer (360^o Perception and Interaction Workshop)

Math for Machine Learning, MCIT-515. Teaching assistant, Summer/2020.
Machine Perception, CIS-580. Teaching assistant, Spring/2018, Spring/2019.
Advanced Robotics, MEAM-620. Teaching assistant, Spring/2017.
Robotics: Planning and Perception, CIS-390. Teaching assistant, Fall/2016.

[ cv | github | scholar | twitter | linkedin ]