Deep Learning

Understanding Normalization in Deep Learning

一个卷积层,一个归一化层,一个非线性激活函数一起构成了深度卷积神经网络 (ConvNet)的“原子”结构。通过该基础结构的堆叠,产生了许多应用广泛的神经网络。归一化方法是这些神经网络的重要组成部分之一。本次报告的内容围绕深度学习的归一化方法展开,及其为神经网络带来的正则能力与泛化能力。报告分为四个部分。第一部以白化网络(Whitened Neural Network,WNN)为例,浅析神经网络前向计算与反向传播的关系:表明修改前向计算,将可以直接影响深度网络的费希尔信息矩阵 (Fisher …

Switchable Normalization

Meta-learning to learn normalization method for each hidden layer in ConvNet.

Learning-to-Learn-to-Normalize: Algorithms, Applications and Theory

Introduce a new family of normalization methods in Deep Learning.

Regularization in BN

Understanding Batch Normalization in deep learning.

浅谈深度学习:归一化中的正则与泛化

Understanding batch normalization in Deep Learning. This blog was written in Chinese.

WIDER Face and Pedestrian Challenge 2018

We organize a new challenge in conjunction with ECCV 2018. The challenge centers around the problem of precise localization of human faces and bodies, and accurate association of identities. It comprises of three tracks: WIDER Face aims at soliciting …

Understanding Normalization

Understanding Normalization Methods in Deep Learning.

Face Image Generation

Image Generation via GANs.

CUImage Dataset

A large-scale dataset for learning general visual representation.

Language Guided Image Segmentation

Joint learning image and language.