Search Results for author: Shufan Li

Found 4 papers, 2 papers with code

Scale-MAE: A Scale-Aware Masked Autoencoder for Multiscale Geospatial Representation Learning

no code implementations30 Dec 2022 Colorado J. Reed, Ritwik Gupta, Shufan Li, Sarah Brockman, Christopher Funk, Brian Clipp, Kurt Keutzer, Salvatore Candido, Matt Uyttendaele, Trevor Darrell

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 with imagery from a range of spatial scales.

Representation Learning

Refine and Represent: Region-to-Object Representation Learning

1 code implementation25 Aug 2022 Akash Gokul, Konstantinos Kallidromitis, Shufan Li, Yusuke Kato, Kazuki Kozuka, Trevor Darrell, Colorado J Reed

Recent works in self-supervised learning have demonstrated strong performance on scene-level dense prediction tasks by pretraining with object-centric or region-based correspondence objectives.

Representation Learning Self-Supervised Learning +2

Interpreting Audiograms with Multi-stage Neural Networks

1 code implementation17 Dec 2021 Shufan Li, Congxi Lu, Linkai Li, Jirong Duan, Xinping Fu, Haoshuai Zhou

Audiograms are a particular type of line charts representing individuals' hearing level at various frequencies.

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