上岸算法 发表于 2021-3-30 23:39:20

上岸 I 计算机视觉领域历年经典Paper

本帖最后由 上岸算法 于 2021-3-30 23:41 编辑

作者简介:
小春老师是上岸算法的Machine Learning和Deep Learning导师,美国常春藤CS毕业,拥有多家FLAG任职经验,现任Machine Learning Scientist,在Deep Learning/Machine Learning/ NLP等领域有多篇paper发表和丰富的业界经验。担任面试官多年,曾帮助多位应届生设计辅导项目,修改简历,模拟面试直至斩获大厂Offer。https://mmbiz.qpic.cn/mmbiz_gif/FIBZec7ucChhZqvOVoz3euT3icYwAAGMrYiaCEa3IwKQ1zxPd5ZrDa6zrocMiccjpdiaY8Rv0ibvcUgYBVgsibXUG4bQ/640?wx_fmt=gif

计算机视觉是AI领域绝对的领头羊,从各大会议开始涌现Deep Learning的论文开始, 到今天应用到行业各个领域百花齐放, Deep Learning绝大多数里程碑式的进展都是从计算机视觉得到突破,并且应用到其他领域的。其原因之一是计算机视觉的信号相对于自然语言等其他信号更加直观, 更加易于被Embed成机器可以识别的模式。计算机视觉是各大公司招聘Research Scientist, Applied Scientist以及Machine Learning Engineer的一个非常重要的方面, 也是我们正在筹备开放的AI课程的必讲及详讲内容。
今天小春老师带大家熟悉一下计算机视觉里程碑式的进展的经典论文。
第一篇: LeCun, Yann, and Yoshua Bengio. "Convolutional networks for images, speech, and time series." The handbook of brain theory and neural networks 3361.10 (1995): 1995. 提出了CNN毫无疑问计算机视觉在Deep Learning领域的一大milestone
第二篇:Krizhevsky, Alex, Ilya Sutskever, and Geoffrey E. Hinton. "Imagenet classification with deep convolutional neural networks." Advances in neural information processing systems. 2012. 提出了AlexNet, 也是绝对的CV@Deep Learning的Breakthrough
第三篇:Simonyan, Karen, and Andrew Zisserman. "Very deep convolutional networks for large-scale image recognition." arXiv preprint arXiv:1409.1556 (2014). 提出了VGGNet使得Neural Networks 变得deep
第四篇:Szegedy, Christian, et al. "Going deeper with convolutions." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2015. GoogLeNet使得Neural Networks 变得very deep
第五篇: He, Kaiming, et al. "Deep residual learning for image recognition." arXiv preprint arXiv:1512.03385 (2015). 当年CVPR best paper, 进一步让Neural Networks 变得更加deep, 现在仍然是各大tech公司答CV系列的万金油
第六篇: Goodfellow, Ian, et al. "Generative adversarial nets." Advances in Neural Information Processing Systems. 2014. 提出了GAN,现在仍然是各大fake狂们膜拜的神作第七篇: Kingma, Diederik P., and Max Welling. "Auto-encoding variational bayes." arXiv preprint arXiv:1312.6114 (2013). 提出了VAE, 是Unsupervised Deep Learning领域非常重要的一篇paper
第八篇:Koch, Gregory, Richard Zemel, and Ruslan Salakhutdinov. "Siamese Neural Networks for One-shot Image Recognition."(2015) 提出了Siamese Neural Networks, 使得在很少量data的情况下,训练一个成功的NeuraNet成为可能
上岸4月份大厂面经公开课


[*]04/05 -小K老师:简历项目深挖+BQ模拟面试
[*]04/07 -米线儿老师:大数据在企业的应用以及工具
[*]04/17 -莎莎老师: 出道即巅峰:转专业上岸亚麻Applied Scientist史
[*]04/19 -小春老师: 推荐系统公开课
[*]04/26 -小雨老师 :SQL 带刷
[*]04/28 -Ginger老师: 疫情下我是如何拿到Facebook DS Offer的?

【6节课免费参与】
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【DS 方向】
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【SDE 方向】
下面的paper则是针对计算机视觉领域不同分支的,就不多介绍了,直接放paper:
Object Detection Szegedy, Christian, Alexander Toshev, and Dumitru Erhan. "Deep neural networks for object detection." Advances in Neural Information Processing Systems. 2013 Girshick, Ross, et al. "Rich feature hierarchies for accurate object detection and semantic segmentation." Proceedings of the IEEE conference on computer vision and pattern recognition. 2014. (RCNN) He, Kaiming, et al. "Spatial pyramid pooling in deep convolutional networks for visual recognition." European Conference on Computer Vision. Springer International Publishing, 2014 Girshick, Ross. "Fast r-cnn." Proceedings of the IEEE International Conference on Computer Vision. 2015. Ren, Shaoqing, et al. "Faster R-CNN: Towards real-time object detection with region proposal networks." Advances in neural information processing systems. 2015 Redmon, Joseph, et al. "You only look once: Unified, real-time object detection." arXiv preprint arXiv:1506.02640 (2015). (YOLO,Oustanding Work, really practical) Liu, Wei, et al. "SSD: Single Shot MultiBox Detector." arXiv preprint arXiv:1512.02325 (2015) Dai, Jifeng, et al. "R-FCN: Object Detection via Region-based Fully Convolutional Networks." arXiv preprint arXiv:1605.06409 (2016) He, Gkioxari, et al. "Mask R-CNN" arXiv preprint arXiv:1703.06870 (2017) Bochkovskiy, Alexey, et al. "YOLOv4: Optimal Speed and Accuracy of Object Detection." arXiv preprint arXiv:2004.10934 (2020). Tan, Mingxing, et al. “EfficientDet: Scalable and Efficient Object Detection." arXiv preprint arXiv:1911.09070 (2019).
Object Segmentation J. Long, E. Shelhamer, and T. Darrell, “Fully convolutional networks for semantic segmentation.” in CVPR, 2015. L.-C. Chen, G. Papandreou, I. Kokkinos, K. Murphy, and A. L. Yuille. "Semantic image segmentation with deep convolutional nets and fully connected crfs." In ICLR, 2015. Pinheiro, P.O., Collobert, R., Dollar, P. "Learning to segment object candidates." In: NIPS. 2015. Dai, J., He, K., Sun, J. "Instance-aware semantic segmentation via multi-task network cascades." in CVPR. 2016 Dai, J., He, K., Sun, J. "Instance-sensitive Fully Convolutional Networks." arXiv preprint arXiv:1603.08678 (2016)






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查看完整版本: 上岸 I 计算机视觉领域历年经典Paper