CV Code | 计算机视觉开源周报 20190505期
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今天正式将每周末盘点计算机视觉开源代码的环节，改名为计算机视觉开源周报，并为此编排了期号，希望把这个栏目坚持做下去，方便以后期数多了之后大家参考索引。
本周最引人瞩目的开源事件就是Google大脑提出的EfficientNet，这篇论文还登上了Google AI Blog，可见官方也认为是得意之作，CV君在论文刊出当天下午就进行了解读，如果你还不了解，欢迎点击查看：
谷歌大脑提出EfficientNet平衡模型扩展三个维度，取得精度-效率的最大化！
另外，52CV曾经报道过的
也开源了：
https://github.com/wvangansbeke/LaneDetection_End2End
欢迎做智能驾驶相关的朋友参考。
还有，旷视科技的
CVPR 2019 | 旷视提出超分辨率新方法Meta-SR：单一模型实现任意缩放因子
终于开源了！这是超分辨率领域的重要趋势，欢迎follow～（地址在本文的评论区）
ICML 2019
卷积网络模型扩展，提高精度，降低计算量，减小模型size
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
Mingxing Tan, Quoc V. Le
https://arxiv.org/abs/1905.11946v1
https://github.com/tensorflow/tpu/tree/master/models/official/efficientnet
RoNIN: Robust Neural Inertial Navigation in the Wild: Benchmark, Evaluations, and New Methods
Hang Yan, Sachini Herath, Yasutaka Furukawa
https://arxiv.org/abs/1905.12853v1
（将开源，还未公布地址）
Learning Navigation Subroutines by Watching Videos
Ashish Kumar, Saurabh Gupta, Jitendra Malik
https://arxiv.org/abs/1905.12612v1
https://ashishkumar1993.github.io/subroutines/
IJCAI 2019
视频分类
Hallucinating Optical Flow Features for Video Classification
Yongyi Tang, Lin Ma, Lianqiang Zhou
https://arxiv.org/abs/1905.11799v1
https://github.com/YongyiTang92/MoNet-Features
Time Series Workshop of ICML 2019
卫星图像时间序列分析
BreizhCrops: A Satellite Time Series Dataset for Crop Type Identification
Marc Rußwurm, Sébastien Lefèvre, Marco Körner
https://arxiv.org/abs/1905.11893v1
https://github.com/TUM-LMF/BreizhCrops
在无标签视频中的自监督目标检测
Toward Self-Supervised Object Detection in Unlabeled Videos
Elad Amrani, Rami Ben-Ari, Tal Hakim, Alex Bronstein
https://arxiv.org/abs/1905.11137v1
（将开源，还未公布地址）
LAW: Learning to Auto Weight
Zhenmao Li, Yichao Wu, Ken Chen, Yudong WU, Shunfeng Zhou, Jiaheng Liu, Junjie Yan
https://arxiv.org/abs/1905.11058v1
（将开源，还未公布地址）
三维重建
DISN: Deep Implicit Surface Network for High-quality Single-view 3D Reconstruction
Qiangeng Xu, Weiyue Wang, Duygu Ceylan, Radomir Mech, Ulrich Neumann
https://arxiv.org/abs/1905.10711v1
http://github.com/laughtervv/DISN
跨分辨率的人脸识别
Cross-Resolution Face Recognition via Prior-Aided Face Hallucination and Residual Knowledge Distillation
Hanyang Kong, Jian Zhao, Xiaoguang Tu, Junliang Xing, Shengmei Shen, Jiashi Feng
https://arxiv.org/abs/1905.10777v1
（将开源，还未公布地址）
Selective Transfer with Reinforced Transfer Network for Partial Domain Adaptation
Zhihong Chen, Chao Chen, Zhaowei Cheng, Ke Fang, Xinyu Jin
https://arxiv.org/abs/1905.10756v1
（将开源，还未公布地址）
域适应注意力模型用于非监督的跨域人员重识别
Domain Adaptive Attention Model for Unsupervised Cross-Domain Person Re-Identification
Yangru Huang, Peixi Peng, Yi Jin, Junliang Xing, Congyan Lang, Songhe Feng
https://arxiv.org/abs/1905.10529v1
（将开源，还未公布地址）
注意力网络
DIANet: Dense-and-Implicit Attention Network
Zhongzhan Huang, Senwei Liang, Mingfu Liang, Haizhao Yang
https://arxiv.org/abs/1905.10671v1
https://github.com/gbup-group/DIANet
高效网络推断
Feature Map Transform Coding for Energy-Efficient CNN Inference
Brian Chmiel, Chaim Baskin, Ron Banner, Evgenii Zheltonozhskii, Yevgeny Yermolin, Alex Karbachevsky, Alex M. Bronstein, Avi Mendelson
https://arxiv.org/abs/1905.10830v1
https://github.com/CompressTeam/TransformCodingInference
ICIP 2019
基于注意力网络模型的RGBD语义分割
ACNet: Attention Based Network to Exploit Complementary Features for RGBD Semantic Segmentation
Xinxin Hu, Kailun Yang, Lei Fei, Kaiwei Wang
https://arxiv.org/abs/1905.10089v1
https://github.com/anheidelonghu/ACNet
拥挤人群计数
PCC Net: Perspective Crowd Counting via Spatial Convolutional Network
Junyu Gao, Qi Wang, Xuelong Li
https://arxiv.org/abs/1905.10085v1
https://github.com/gjy3035/PCC-Net
ICIP 2019
Multi-level Texture Encoding and Representation (MuLTER) based on Deep Neural Networks
Yuting Hu, Zhiling Long, Ghassan AlRegib
https://arxiv.org/abs/1905.09907v1
https://github.com/olivesgatech
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