116 citations · 162 across the 5 of their papers we have counts for
6 papers
Scale-MAE: A Scale-Aware Masked Autoencoder for Multiscale Geospatial Representation Learning
Colorado J. Reed, Ritwik Gupta, Shufan Li +7
Large, pretrained models are commonly finetuned with imagery that is heavily augmented to mimic different conditions and scales, with the resulting models used for various tasks wi…
AdsorbML: A Leap in Efficiency for Adsorption Energy Calculations using Generalizable Machine Learning Potentials
Janice Lan, Aini Palizhati, Muhammed Shuaibi +6
Computational catalysis is playing an increasingly significant role in the design of catalysts across a wide range of applications. A common task for many computational methods is…
A Practical Stereo Depth System for Smart Glasses
Jialiang Wang, Daniel Scharstein, Akash Bapat +11
We present the design of a productionized end-to-end stereo depth sensing system that does pre-processing, online stereo rectification, and stereo depth estimation with a fallback…
ChamNet: Towards Efficient Network Design through Platform-Aware Model Adaptation
Xiaoliang Dai, Peizhao Zhang, Bichen Wu +10
This paper proposes an efficient neural network (NN) architecture design methodology called Chameleon that honors given resource constraints. Instead of developing new building blo…
Deep Burst Denoising
Clément Godard, Kevin Matzen, Matt Uyttendaele
Noise is an inherent issue of low-light image capture, one which is exacerbated on mobile devices due to their narrow apertures and small sensors. One strategy for mitigating noise…
Real-time Image-based 6-DOF Localization in Large-Scale Environments
Hyon Lim, Sudipta Sinha, Michael Cohen +1
We present a real-time approach for image-based localization within large scenes that have been reconstructed offline using structure from motion (Sfm). From monocular video, our m…