点击我爱计算机视觉标星,更快获取CVML新技术
CV君汇总了过去一周计算机视觉领域新出的开源代码,涉及到图像增广、医学图像分割、图像恢复、目标检测、语义分割、超分辨率、显著目标检测、轻量级网络结构设计、网络规范化、标注工具等,其中有多篇来自CVPR 2019与ICML 2019的论文代码。
希望对你有帮助~
ICML 2019
mixup图像增广,噪声标签建模改进网络训练
Unsupervised label noise modeling and loss correction
Eric Arazo, Diego Ortego, Paul Albert, Noel E. O'Connor, Kevin McGuinness
https://arxiv.org/abs/1904.11238v1
https://github.com/PaulAlbert31/LabelNoiseCorrection
医学图像分割,用于脑核磁图像分割的无监督深度学习
Unsupervised deep learning for Bayesian brain MRI segmentation
Adrian V. Dalca, Evan Yu, Polina Golland, Bruce Fischl, Mert R. Sabuncu, Juan Eugenio Iglesias
https://arxiv.org/abs/1904.11319v1
http://voxelmorph.mit.edu/
ICML 2019
反锯齿模块改进网络的平移不变性
Making Convolutional Networks Shift-Invariant Again
Richard Zhang
https://arxiv.org/abs/1904.11486v1
https://richzhang.github.io/antialiased-cnns/
轻量级网络设计,全局上下文网络超越NLNet与SENet
GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond
Yue Cao, Jiarui Xu, Stephen Lin, Fangyun Wei, Han Hu
https://arxiv.org/abs/1904.11492v1
https://github.com/xvjiarui/GCNet
使用深度学习构建用于稀疏表示学习分类的新方法,超越目前state-of-the-art
IEEE Signal Processing Letters, 2019
Deep Sparse Representation-based Classification
Mahdi Abavisani, Vishal M. Patel
https://arxiv.org/abs/1904.11093v1
http://github.com/mahdiabavisani/DSRC
使用目标中心点进行目标检测、3D检测、姿态估计,Github超870颗星
Objects as Points
Xingyi Zhou, Dequan Wang, Philipp Krähenbühl
https://arxiv.org/abs/1904.07850v2
https://github.com/xingyizhou/CenterNet
整全观大规模视频理解数据集与示例代码
Holistic Large Scale Video Understanding
Ali Diba, Mohsen Fayyaz, Vivek Sharma, Manohar Paluri, Jurgen Gall, Rainer Stiefelhagen, Luc Van Gool
https://arxiv.org/abs/1904.11451v1
https://www.esat.kuleuven.be/
CVPR 2019
语义分割域适应
Bidirectional Learning for Domain Adaptation of Semantic Segmentation
Yunsheng Li, Lu Yuan, Nuno Vasconcelos
https://arxiv.org/abs/1904.10620v1
https://github.com/liyunsheng13/BDL
语义分割的预测学习
Segmenting the Future
Hsu-kuang Chiu, Ehsan Adeli, Juan Carlos Niebles
https://arxiv.org/abs/1904.10666v1
https://github.com/eddyhkchiu/segmenting_the_future/
人体形状估计
Detailed Human Shape Estimation from a Single Image by Hierarchical Mesh Deformation
Hao Zhu, Xinxin Zuo, Sen Wang, Xun Cao, Ruigang Yang
https://arxiv.org/abs/1904.10506v1
https://github.com/zhuhao-nju/hmd.git
用于真实图像超分辨率的多尺度深度学习
Multi-scale deep neural networks for real image super-resolution
Shangqi Gao, Xiahai Zhuang
https://arxiv.org/abs/1904.10698v1
https://github.com/shangqigao/gsq-image-SR
VGG 图像标注软件,支持目标检测语义分割的标注
The VGG Image Annotator (VIA)
Abhishek Dutta, Andrew Zisserman
https://arxiv.org/abs/1904.10699v1
http://www.robots.ox.ac.uk/~vgg/software/via/
用于高效视觉引导的机器人重排列规划的蒙特卡洛树搜索
Monte-Carlo Tree Search for Efficient Visually Guided Rearrangement Planning
Sergey Zagoruyko, Yann Labbé, Igor Kalevatykh, Ivan Laptev, Justin Carpentier, Mathieu Aubry, Josef Sivic
https://arxiv.org/abs/1904.10348v1
https://github.com/ylabbe/rearrangement-planning
学习网络路径搜索用于图像恢复,出自商汤
Path-Restore: Learning Network Path Selection for Image Restoration
Ke Yu, Xintao Wang, Chao Dong, Xiaoou Tang, Chen Change Loy
https://arxiv.org/abs/1904.10343v1
https://yuke93.github.io/Path-Restore/
使用脑电波数据与深度残差网络监控睡眠
End-to-end Sleep Staging with Raw Single Channel EEG using Deep Residual ConvNets
Ahmed Imtiaz Humayun, Asif Shahriyar Sushmit, Taufiq Hasan, Mohammed Imamul Hassan Bhuiyan
https://arxiv.org/abs/1904.10255v1
https://github.com/mHealthBuet/ASSC
神经架构搜索,网络压缩
Towards Learning of Filter-Level Heterogeneous Compression of Convolutional Neural Networks
Yochai Zur, Chaim Baskin, Evgenii Zheltonozhskii, Brian Chmiel, Itay Evron, Alex M. Bronstein
https://arxiv.org/abs/1904.09872v1
https://github.com/yochaiz/Slimmable
https://github.com/yochaiz/darts-UNIQ
自动时域一致性的视频彩色化
Automatic Temporally Coherent Video Colorization
Harrish Thasarathan, Kamyar Nazeri, Mehran Ebrahimi
https://arxiv.org/abs/1904.09527v1
https://github.com/Harry-Thasarathan/TCVC
CVPR 2019
简单的池化设计用于实时显著目标检测
A Simple Pooling-Based Design for Real-Time Salient Object Detection
Jiang-Jiang Liu, Qibin Hou, Ming-Ming Cheng, Jiashi Feng, Jianmin Jiang
https://arxiv.org/abs/1904.09569v1
http://mmcheng.net/poolnet/
几何感知的非监督图像翻译
TransGaGa: Geometry-Aware Unsupervised Image-to-Image Translation
Wayne Wu, Kaidi Cao, Cheng Li, Chen Qian, Chen Change Loy
https://arxiv.org/abs/1904.09571v1
https://wywu.github.io/projects/TGaGa/TGaGa.html
网络Normalization新方法,出自商汤
Switchable Whitening for Deep Representation Learning
Xingang Pan, Xiaohang Zhan, Jianping Shi, Xiaoou Tang, Ping Luo
https://arxiv.org/abs/1904.09739v1
(将要开源,还未公布地址)
显著目标检测综述
Salient Object Detection in the Deep Learning Era: An In-Depth Survey
Wenguan Wang, Qiuxia Lai, Huazhu Fu, Jianbing Shen, Haibin Ling
https://arxiv.org/abs/1904.09146v1
https://github.com/wenguanwang/SODsurvey
MIDL 2019
医学图像分割,肺部分割
XLSor: A Robust and Accurate Lung Segmentor on Chest X-Rays Using Criss-Cross Attention and Customized Radiorealistic Abnormalities Generation
Youbao Tang, Yuxing Tang, Jing Xiao, Ronald M. Summers
https://arxiv.org/abs/1904.09229v1
https://github.com/rsummers11/CADLab/tree/master/Lung_Segmentation_XLSor
CVPR 2019 workshops on explainable AI
深度神经决策森林的决策处理可视化
Visualizing the decision-making process in deep neural decision forest
Shichao Li, Kwang-Ting Cheng
https://arxiv.org/abs/1904.09201v1
https://github.com/Nicholasli1995/VisualizingNDF
LATTE:用于LiDAR点云的开源标注工具
LATTE: Accelerating LiDAR Point Cloud Annotation via Sensor Fusion, One-Click Annotation, and Tracking
Bernie Wang, Virginia Wu, Bichen Wu, Kurt Keutzer
https://arxiv.org/abs/1904.09085v1
https://github.com/bernwang/latte
使用深度学习进行服装设计,好有趣的方向。
Fashion++: Minimal Edits for Outfit Improvement
Wei-Lin Hsiao, Isay Katsman, Chao-Yuan Wu, Devi Parikh, Kristen Grauman
https://arxiv.org/abs/1904.09261v1
http://vision.cs.utexas.edu/projects/FashionPlus
支持CV君,请文末点个“在看”,谢谢~
更多之前代码汇总:
CV Code | 本周新出计算机视觉开源代码汇总(含图像修复、目标检测、医学图像分割、度量学习等)
CV Code | 本周新出计算机视觉开源代码汇总(含实例分割、行人检测、姿态估计、神经架构搜索、超分辨率等)
本周新出开源计算机视觉代码汇总(含图像超分辨、视频目标分割、行人重识别、点云识别等)
CV Code | 本周计算机视觉新出开源代码汇总(含医学图像分割、神经架构搜索、姿态迁移、超分辨率等)
今日新出 CV 论文汇总(含医学图像、目标检测、唇语识别、SLAM等)
CV Code | 本周计算机视觉新出开源代码汇总(含目标检测、深度估计、视频识别、网络加速算法等)
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