56 citations · 151 across the 5 of their papers we have counts for
5 papers
AVT: Unsupervised Learning of Transformation Equivariant Representations by Autoencoding Variational Transformations
Guo-Jun Qi, Liheng Zhang, Chang Wen Chen +1
The learning of Transformation-Equivariant Representations (TERs), which is introduced by Hinton et al. \cite{hinton2011transforming}, has been considered as a principle to reveal…
AET vs. AED: Unsupervised Representation Learning by Auto-Encoding Transformations rather than Data
Liheng Zhang, Guo-Jun Qi, Liqiang Wang +1
The success of deep neural networks often relies on a large amount of labeled examples, which can be difficult to obtain in many real scenarios. To address this challenge, unsuperv…
Gated Context Aggregation Network for Image Dehazing and Deraining
Dongdong Chen, Mingming He, Qingnan Fan +5
Image dehazing aims to recover the uncorrupted content from a hazy image. Instead of leveraging traditional low-level or handcrafted image priors as the restoration constraints, e.…
CapProNet: Deep Feature Learning via Orthogonal Projections onto Capsule Subspaces
Liheng Zhang, Marzieh Edraki, Guo-Jun Qi
In this paper, we formalize the idea behind capsule nets of using a capsule vector rather than a neuron activation to predict the label of samples. To this end, we propose to learn…
Global versus Localized Generative Adversarial Nets
Guo-Jun Qi, Liheng Zhang, Hao Hu +3
In this paper, we present a novel localized Generative Adversarial Net (GAN) to learn on the manifold of real data. Compared with the classic GAN that {\em globally} parameterizes…