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Info Title: Neural Discrete Representation Learning Task: Image Generation Author: A. van den Oord, O. Vinyals, and K. Kavukcuoglu Date: Nov. 2017 Arxiv: 1711.00937 Published: NIPS 2017 Affiliation: Google DeepMind Highlights & Drawbacks Discrete representation for data distribution The prior is learned instead of rando...

Info Title: CondenseNet: An Efficient DenseNet using Learned Group Convolutions Task: Image Classification Author: Gao Huang, Shichen Liu, Laurens van der Maaten, Kilian Q. Weinberger Date: Nov. 2017 Arxiv: 1711.09224 Published: CVPR 2018 Highlights & Drawbacks Learned manner for group hyper-params Implementation with sta...

Info Title: Fast RCNN Task: Object Detection Author: Ross Girshick Arxiv: 1504.08083 Date: April 2015 Published: ICCV 2015 Highlights An improvement to [R-CNN] (https://blog.ddlee.cn/posts/415f4992/), ROI Pooling Design Article structure is clear Motivation & Design R-CNN’s Drawbacks Training is a multi-stage proc...

Info Title: R-FCN: Object Detection via Region-based Fully Convolutional Networks Task: Object Detection Author: Jifeng Dai, Yi Li, Kaiming He, and Jian Sun Arxiv: 1605.06409 Published: NIPS 2016 Highlights Full convolutional network, sharing weights across ROIs Motivation & Design The article points out that there is an un...

Info Title: Towards Instance-level Image-to-Image Translation Task: Image Translation Author: Zhiqiang Shen, Mingyang Huang, Jianping Shi, Xiangyang Xue, Thomas Huang Date: May 2019 Arxiv: 1905.01744 Published: CVPR 2019 Highlights & Drawbacks The instance-level objective loss can help learn a more accurate reconstruction a...

Info Title: DSOD: learning deeply supervised object detectors from scratch Task: Object Detection Author: Z. Shen, Z. Liu, J. Li, Y. Jiang, Y. Chen, and X. Xue Date: Aug. 2017 Arxiv: 1708.01241 Published: ICCV 2017 Highlights & Drawbacks Object Detection without pre-training DenseNet-like network Motivation & Desi...

Info Title: On-the-fly Operation Batching in Dynamic Computation Graphs Author: Graham Neubig, Yoav Goldberg, Chris Dyer Arxiv: 1705.07860 Date: May. 2017 Highlights & Drawbacks Batch computation on dynamic graph Motivation & Design Dynamic learning-based deep learning frameworks such as Pytorch, DyNet provide a more flexibl...

Info Title: GlyphGAN: Style-Consistent Font Generation Based on Generative Adversarial Networks Task: Font Generation Author: H. Hayashi, K. Abe, and S. Uchida Date: May 2019 Arxiv: 1905.12502 Highlights & Drawbacks Two encode vectors for character and style, respectively Motivation & Design The main frame work is a D...