Original Works

Publications

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

  Colorado Reed*, Shufan Li*, Ritwik Gupta*, Sarah Brockman, Christopher Funk, Brian Clipp, Kurt Keutzer, Salvatore Candido, Matt Uyttendaele, Trevor Darrell

  [Arxiv]. ICCV 2023. (Oral)

  Scale-Aware representation learning with prior information of image scale.
• Hierarchical Open-vocabulary Universal Image Segmentation.

  Xudong Wang*, Shufan Li*, Konstantinos Kallidromitis*, Yusuke Kato, Kazuki Kozuka, Trevor Darrell

  [Arxiv]. NeurIPS 2023.

  Segmentating arbritrary objects and object parts using text prompts

Under Review

• Refine and Represent: Region-to-Object Representation Learning

  Akash Gokul*, Konstantinos Kallidromitis*, Shufan Li*, Yusuke Kato, Kazuki Kozuka, Trevor Darrell, Colorado J Reed

  [preprint]. 2022.

  Representation learning benefits by first learning from image regions and then learning from actual objects.

Technical Reports

• Interpreting Audiograms with Multi-stage Neural Networks

  Shufan Li*, Congxi Lu, Linkai Li,Jirong Duan, Xinping Fu, Haoshuai Zhou

  [Arxiv]. 2021.

  Accelerate Hearing Aid Fitting using Computer Vision
• Chart-RCNN: Efficient Line Chart Data Extraction from Camera Images

  Shufan Li*, Congxi Lu, Linkai Li, Haoshuai Zhou

  [preprint]. 2022.

  Line Chart Data Extraction in the wild.