1 code implementation • 28 Aug 2023 • Ran Liu, Sahil Khose, Jingyun Xiao, Lakshmi Sathidevi, Keerthan Ramnath, Zsolt Kira, Eva L. Dyer
To address this challenge, we propose a novel approach for distribution-aware latent augmentation that leverages the relationships across samples to guide the augmentation procedure.
1 code implementation • 1 Jan 2023 • Jorge Quesada, Lakshmi Sathidevi, Ran Liu, Nauman Ahad, Joy M. Jackson, Mehdi Azabou, Jingyun Xiao, Christopher Liding, Matthew Jin, Carolina Urzay, William Gray-Roncal, Erik C. Johnson, Eva L. Dyer
To bridge this gap, we introduce a new dataset, annotations, and multiple downstream tasks that provide diverse ways to readout information about brain structure and architecture from the same image.
1 code implementation • 10 Jun 2022 • Ran Liu, Mehdi Azabou, Max Dabagia, Jingyun Xiao, Eva L. Dyer
By enabling flexible pre-training that can be transferred to neural recordings of different size and order, our work provides a first step towards creating a foundation model for neural decoding.
no code implementations • The ActivityNet Large-Scale Activity Recognition Challenge Workshop, CVPR 2019 • Yuanhang Zhang, Jingyun Xiao, Shuang Yang, Shiguang Shan
This report describes the approach underlying our submission to the active speaker detection task (task B-2) of ActivityNet Challenge 2019.
Ranked #17 on Audio-Visual Active Speaker Detection on AVA-ActiveSpeaker (using extra training data)