17 citations · 31 across the 3 of their papers we have counts for
3 papers
cs.CV2021★ 17 cited
Learning to Focus: Cascaded Feature Matching Network for Few-shot Image Recognition
Mengting Chen, Xinggang Wang, Heng Luo +2
Deep networks can learn to accurately recognize objects of a category by training on a large number of annotated images. However, a meta-learning challenge known as a low-shot imag…
cs.CV2019
Diversity Transfer Network for Few-Shot Learning
Mengting Chen, Yuxin Fang, Xinggang Wang +6
Few-shot learning is a challenging task that aims at training a classifier for unseen classes with only a few training examples. The main difficulty of few-shot learning lies in th…
cs.LG2012★ 14 cited
Texture Modeling with Convolutional Spike-and-Slab RBMs and Deep Extensions
Heng Luo, Pierre Luc Carrier, Aaron Courville +1
We apply the spike-and-slab Restricted Boltzmann Machine (ssRBM) to texture modeling. The ssRBM with tiled-convolution weight sharing (TssRBM) achieves or surpasses the state-of-th…