点击我爱计算机视觉标星,更快获取CVML新技术
计算机视觉技术发展迅速,很多时候,可悲的不是我们没有努力,而是没有跟上时代的步伐。努力coding终于出来结果了,却发现早就有人开源了,效果还比自己写的好!
CV君汇总了最近过去的一周新出的开源代码,包括方向有目标检测、深度估计、行人重识别、实例分割、姿态估计、超分辨率、行人检测、神经架构搜索等,还有一些新出的机器学习范式如长尾识别问题。希望对大家有启发。
ps.以下列出的代码网址中,有少部分代码还未放出。
Instance Segmentation of Biological Images Using Harmonic Embeddings
Victor Kulikov, Victor Lempitsky
https://arxiv.org/abs/1904.05257v1
https://github.com/kulikovv/harmonic
CVPR 2019 Oral
Large-Scale Long-Tailed Recognition in an Open World
Ziwei Liu, Zhongqi Miao, Xiaohang Zhan, Jiayun Wang, Boqing Gong, Stella X. Yu
https://arxiv.org/abs/1904.05160v1
https://liuziwei7.github.io/projects/LongTail.html
Spherical Regression: Learning Viewpoints, Surface Normals and 3D Rotations on n-Spheres
Shuai Liao, Efstratios Gavves, Cees G. M. Snoek
https://arxiv.org/abs/1904.05404v1
https://github.com/leoshine/Spherical_Regression
CVPR 2019
Expressive Body Capture: 3D Hands, Face, and Body from a Single Image
Georgios Pavlakos, Vasileios Choutas, Nima Ghorbani, Timo Bolkart, Ahmed A. A. Osman, Dimitrios Tzionas, Michael J. Black
https://arxiv.org/abs/1904.05866v1
https://smpl-x.is.tue.mpg.de/
Two Body Problem: Collaborative Visual Task Completion
Unnat Jain, Luca Weihs, Eric Kolve, Mohammad Rastegari, Svetlana Lazebnik, Ali Farhadi, Alexander Schwing, Aniruddha Kembhavi
https://arxiv.org/abs/1904.05879v1
https://prior.allenai.org/projects/two-body-problem
Generating Multiple Hypotheses for 3D Human Pose Estimation with Mixture Density Network
Chen Li, Gim Hee Lee
https://arxiv.org/abs/1904.05547v1
https://github.com/chaneyddtt/Generating-Multiple-Hypotheses-for-3D-Human-Pose-Estimation-with-Mixture-Density-Network
Generalizing Monocular 3D Human Pose Estimation in the Wild
Luyang Wang, Yan Chen, Zhenhua Guo, Keyuan Qian, Mude Lin, Hongsheng Li, Jimmy S. Ren
https://arxiv.org/abs/1904.05512
https://github.com/llcshappy/Monocular-3D-Human-Pose
CVPR 2019
Reliable and Efficient Image Cropping: A Grid Anchor based Approach
Hui Zeng, Lida Li, Zisheng Cao, Lei Zhang
https://arxiv.org/abs/1904.04441v1
https://github.com/HuiZeng/Grid-Anchor-based-Image-Cropping
High-Resolution Representations for Labeling Pixels and Regions
Ke Sun, Yang Zhao, Borui Jiang, Tianheng Cheng, Bin Xiao, Dong Liu, Yadong Mu, Xinggang Wang, Wenyu Liu, Jingdong Wang
https://arxiv.org/abs/1904.04514v1
https://github.com/HRNet
Adversarial Learning of Disentangled and Generalizable Representations for Visual Attributes
James Oldfield, Yannis Panagakis, Mihalis A. Nicolaou
https://arxiv.org/abs/1904.04772v1
https://github.com/james-oldfield/adv-attribute-disentanglement
Adaptive Morphological Reconstruction for Seeded Image Segmentation
Tao Lei, Xiaohong Jia, Tongliang Liu, Shigang Liu, Hongying Meng, Asoke K. Nandi
https://arxiv.org/abs/1904.03973v1
https://github.com/SUST-reynole/AMR
CVPR 2019
Learning monocular depth estimation infusing traditional stereo knowledge
Fabio Tosi, Filippo Aleotti, Matteo Poggi, Stefano Mattoccia
https://arxiv.org/abs/1904.04144v1
https://github.com/fabiotosi92/monoResMatch-Tensorflow
CVPR 2019
Adaptively Connected Neural Networks
Guangrun Wang, Keze Wang, Liang Lin
https://arxiv.org/abs/1904.03579
https://github.com/wanggrun/Adaptively-Connected-Neural-Networks
Weakly Supervised Person Re-identification: Cost-effective Learning with A New Benchmark
Guangrun Wang, Guangcong Wang, Xujie Zhang, Jianhuang Lai, Liang Lin
https://arxiv.org/abs/1904.03845v1
https://github.com/wanggrun/SYSU-30k
CVPR 2019
Self-supervised Spatio-temporal Representation Learning for Videos by Predicting Motion and Appearance Statistics
Jiangliu Wang, Jianbo Jiao, Linchao Bao, Shengfeng He, Yunhui Liu, Wei Liu
https://arxiv.org/abs/1904.03597v1
https://github.com/laura-wang/video_repres_mas
Stokes Inversion based on Convolutional Neural Networks
A. Asensio Ramos , C. Diaz Baso
https://arxiv.org/abs/1904.03714v1
http://github.com/aasensio/sicon
CVPR 2019
Camera Lens Super-Resolution
Chang Chen, Zhiwei Xiong, Xinmei Tian, Zheng-Jun Zha, Feng Wu
https://arxiv.org/abs/1904.03378v1
https://github.com/ngchc/CameraSR
When AWGN-based Denoiser Meets Real Noises
Yuqian Zhou, Jianbo Jiao, Haibin Huang, Yang Wang, Jue Wang, Honghui Shi, Thomas Huang
https://arxiv.org/abs/1904.03485v1
https://github.com/yzhouas/PD-Denoising-pytorch
Doodle to Search: Practical Zero-Shot Sketch-based Image Retrieval
Sounak Dey, Pau Riba, Anjan Dutta, Josep Llados, Yi-Zhe Song
https://arxiv.org/abs/1904.03451v1
https://sounakdey.github.io/doodle2search.github.io/
Instance-Level Meta Normalization
Songhao Jia, Ding-Jie Chen, Hwann-Tzong Chen
https://arxiv.org/abs/1904.03516v1
https://github.com/Gasoonjia/ILM-Norm
The EntOptLayout Cytoscape plug-in for the efficient visualization of major protein complexes in protein-protein interaction and signalling networks
Bence Agg, Andrea Csaszar, Mate Szalay-Beko, Daniel V. Veres, Reka Mizsei, Peter Ferdinandy, Peter Csermely, Istvan A. Kovacs
https://arxiv.org/abs/1904.03910v1
http://apps.cytoscape.org/apps/entoptlayout
Can GCNs Go as Deep as CNNs?
Guohao Li, Matthias Müller, Ali Thabet, Bernard Ghanem
https://arxiv.org/abs/1904.03751v1
https://sites.google.com/view/deep-gcns
LP-3DCNN: Unveiling Local Phase in 3D Convolutional Neural Networks
Sudhakar Kumawat, Shanmuganathan Raman
https://arxiv.org/abs/1904.03498v1
https://sites.google.com/view/lp-3dcnn/home
Branched Multi-Task Networks: Deciding What Layers To Share
Simon Vandenhende, Bert De Brabandere, Luc Van Gool
https://arxiv.org/abs/1904.02920v1
https://github.com/SimonVandenhende/
3D LiDAR and Stereo Fusion using Stereo Matching Network with Conditional Cost Volume Normalization
Tsun-Hsuan Wang, Hou-Ning Hu, Chieh Hubert Lin, Yi-Hsuan Tsai, Wei-Chen Chiu, Min Sun
https://arxiv.org/abs/1904.02917v1
https://zswang666.github.io/Stereo-LiDAR-CCVNorm-Project-Page/
https://github.com/zswang666/Stereo-LiDAR-CCVNorm
CVPR 2019
High-level Semantic Feature Detection:A New Perspective for Pedestrian Detection
Wei Liu, Shengcai Liao, Weiqiang Ren, Weidong Hu, Yinan Yu
https://arxiv.org/abs/1904.02948v1
https://github.com/liuwei16/CSP
Single-Path NAS: Designing Hardware-Efficient ConvNets in less than 4 Hours
Dimitrios Stamoulis, Ruizhou Ding, Di Wang, Dimitrios Lymberopoulos, Bodhi Priyantha, Jie Liu, Diana Marculescu
https://arxiv.org/abs/1904.02877v1
https://github.com/dstamoulis/single-path-nas
Point-to-Point Video Generation
Tsun-Hsuan Wang, Yen-Chi Cheng, Chieh Hubert Lin, Hwann-Tzong Chen, Min Sun
https://arxiv.org/abs/1904.02912v1
https://zswang666.github.io/P2PVG-Project-Page/
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