这篇涉及到以下三篇论文: Unpaired Image Captioning by Language Pivoting (ECCV 2018) Show, Tell and Discriminate: Image Captioning by Self-retrieval with Partially Labeled Data (ECCV 2018) Unsupervised Image Caption (CVPR 2019) 1. Unpaired Image Captioning by Lan…

Image caption generation: https://github.com/eladhoffer/captionGen Simple encoder-decoder image captioning: https://github.com/udacity/CVND---Image-Captioning-Project (Paper)StyleNet: Generating Attractive Visual Captions with Styles:  https://github…

Awesome Image Captioning 2018-12-03 19:19:56 From: https://github.com/zhjohnchan/awesome-image-captioning Papers 2010 I2t: Image parsing to text description - Yao B Z et al, P IEEE 2011. 2011 Im2Text: Describing Images Using 1 Million Captioned Photo…

Code Address:https://github.com/junyanz/CycleGAN. Abstract 引出Image Translating的概念(greyscale to color, image to semantic labels, edge-map to photograph.),并申明了本作的动机,不使用 image pairs来训练图片的风格转换:We present an approach for learning to translate an image fro…

Image Caption: Automatically describing the content of an image domain:CV+NLP Category:(by myself, you can read the survey for detail.) CNN+RNN, with attention mechanisms Reinforcement Learning GAN Compositional Architecture: Review Network, Guiding…

1.Unsupervised learning of video representations using LSTMs 方法:从先前的帧编码预测未来帧序列 相似于Sequence to sequence learning with neural networks论文 方法:使用一个LSTM编码输入文本成固定表示,另一个LSTM解码成不同语言 2.Describing Videos by Exploiting Temporal Structure 该论文发表在iccv2015,是第一篇使用时间关…

来源:http://blog.csdn.net/abcjennifer/article/details/7804962 无监督学习近年来很热,先后应用于computer vision, audio classification和 NLP等问题,通过机器进行无监督学习feature得到的结果,其accuracy大多明显优于其他方法进行training.本文将主要针对Andrew的unsupervised learning,结合他的视频:unsupervised feature learning b…

1    Unsupervised Learning 1.1    k-means clustering algorithm 1.1.1    算法思想 1.1.2    k-means的不足之处 1.1.3    如何选择K值 1.1.4    Spark MLlib 实现 k-means 算法 1.2    Mixture of Gaussians and the EM algorithm 1.3    The EM Algorithm 1.4    Principal Components…

Deep Recurrent Q-Learning for Partially Observable MDPs  摘要:DQN 的两个缺陷,分别是:limited memory 和 rely on being able to perceive the complete game screen at each decision point. 为了解决这两个问题,本文尝试用 LSTM 单元 替换到后面的 fc layer,这样就产生了 Deep Recurrent Q-Network (DRQN),…

Idea Points (data) in same cluster are near each others, or are connected by each others. So: For a distance d,every points in a cluster always can find some points in the same cluster. Distances between points in difference clusters are bigger than…