115 citations · 207 across the 8 of their papers we have counts for
10 papers
A scalable system to measure contrail formation on a per-flight basis
Scott Geraedts, Erica Brand, Thomas R. Dean +12
Persistent contrails make up a large fraction of aviation's contribution to global warming. We describe a scalable, automated detection and matching (ADM) system to determine from…
OpenContrails: Benchmarking Contrail Detection on GOES-16 ABI
Joe Yue-Hei Ng, Kevin McCloskey, Jian Cui +6
Contrails (condensation trails) are line-shaped ice clouds caused by aircraft and are likely the largest contributor of aviation-induced climate change. Contrail avoidance is poten…
A simple, efficient and scalable contrastive masked autoencoder for learning visual representations
Shlok Mishra, Joshua Robinson, Huiwen Chang +4
We introduce CAN, a simple, efficient and scalable method for self-supervised learning of visual representations. Our framework is a minimal and conceptually clean synthesis of (C)…
Unsupervised Disentanglement without Autoencoding: Pitfalls and Future Directions
Andrea Burns, Aaron Sarna, Dilip Krishnan +1
Disentangled visual representations have largely been studied with generative models such as Variational AutoEncoders (VAEs). While prior work has focused on generative methods for…
Supervised Contrastive Learning
Prannay Khosla, Piotr Teterwak, Chen Wang +6
Contrastive learning applied to self-supervised representation learning has seen a resurgence in recent years, leading to state of the art performance in the unsupervised training…
Local Deep Implicit Functions for 3D Shape
Kyle Genova, Forrester Cole, Avneesh Sud +2
The goal of this project is to learn a 3D shape representation that enables accurate surface reconstruction, compact storage, efficient computation, consistency for similar shapes,…
Boundless: Generative Adversarial Networks for Image Extension
Piotr Teterwak, Aaron Sarna, Dilip Krishnan +4
Image extension models have broad applications in image editing, computational photography and computer graphics. While image inpainting has been extensively studied in the literat…
Learning Shape Templates with Structured Implicit Functions
Kyle Genova, Forrester Cole, Daniel Vlasic +3
Template 3D shapes are useful for many tasks in graphics and vision, including fitting observation data, analyzing shape collections, and transferring shape attributes. Because of…
Unsupervised Training for 3D Morphable Model Regression
Kyle Genova, Forrester Cole, Aaron Maschinot +3
We present a method for training a regression network from image pixels to 3D morphable model coordinates using only unlabeled photographs. The training loss is based on features f…
Synthesizing Normalized Faces from Facial Identity Features
Forrester Cole, David Belanger, Dilip Krishnan +3
We present a method for synthesizing a frontal, neutral-expression image of a person's face given an input face photograph. This is achieved by learning to generate facial landmark…