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Tutorial Material for ICCV19 Proposal
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00_setup Delete README.ipynb Feb 14, 2019
01_basics init commit Feb 14, 2019
02_classification init commit Feb 14, 2019
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05_deployment add deployment Feb 19, 2019
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LICENSE Initial commit Feb 14, 2019 tittle Feb 22, 2019

ICCV19 Seoul Tutorial : Everything You Need to Know to Reproduce SOTA Deep Learning Models from Hands-on Tutorial (Proposing)

Time: TBD

Location: TBD

Organizers: Hang Zhang, Tong He, Zhi Zhang, Zhongyue Zhang, Haibin Lin, Aston Zhang, Mu Li


Deep Learning has become the de facto standard algorithm in computer vision. There are a surge amount of approaches being proposed every year for different tasks. Reproducing the complete system in every single detail can be problematic and time-consuming, especially for the beginners. Existing open-source implementations are typically not well-maintained and the code can be easily broken by the rapid updates of the deep learning frameworks. In this tutorial, we will walk through the technical details of the state-of-the-art (SOTA) algorithms in major computer vision tasks, and we also provide the code implementations and hands-on tutorials to reproduce the large-scale training in this tutorial.


Time Title Slides Notebooks
8:00-8:15 Welcome and AWS Setup link link
8:15-8:30 Deep Learning and Gluon Basics (NDArray, AutoGrad, Libraries) link,link
8:30-9:30 Bags of Tricks for Image Classification (ResNet, MobileNet, Inception) link link
9:30-10:30 Understanding Object Detectors (SSD, Faster RCNN, YOLOV3) link link
10:30-11:30 Semantic segmentation algorithms (FCN, PSPNet, DeepLabV3) link link
11:30-12:00 Painless Deployment (C++, TVM) link,link
12:00-12:15 Q&A and Closing
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