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<html>
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<title>CS 763: Computer Vision (Deep Learning), Spring 2017</title>
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<TABLE cellspacing="2" cellpadding="14" width="1100" border="0">
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<H2>CS 763 - Computer Vision </H2>
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<H3><font color = "#777777">Course Information</font></H3>
Please refer to the <a href="https://www.cse.iitb.ac.in/~ajitvr/CS763_Spring2017/">CS763 Spring 2017</a> course page for general information. On this page, you will find specific information for the 8 lectures to be taught be <a href="http://cse.iit.ac.in/~ajain/">Prof. Arjun Jain</a>.
<H3><font color = "#777777">Course Information</font></H3>
<ul>
<li><b>Instructor:</b> Arjun Jain
<li><b>Office:</b> 216, CSE New Building
<li><b>Email:</b> <i>ajain@cse DOT iitb DOT ac DOT in</i>
<li><b>Instructor Office Hours (in room 216 CSE New Building):</b> Prof. Arjun Jain is on campus only on Fridays (and Saturdays for the duration of this part of the course). Meet him after class or fix an appointment over email
<H3><font color = "#777777">Topics to be covered (tentative list)</font></H3>
<UL>
<li> The data driven paradigm, feed forwards networks, back propagation and chain rule
<li> CNNs and their building blocks - ReLU, MaxPool, Convolution, MSECriterion, CrossEntropy and SoftMax
<li> Vanishing gradients, residual blocks, visualizing and understanding CNNs
<li> CNN applications, CNN compression
<li> Siamese and triplet networks, (and if time permits) generative models: deep dream, neural art and GANs
</UL>
<HR>
<H3><font color = "#777777">Learning materials and textbooks</font></H3>
<ul>
<li> Lecture slides that will be regularly posted
<li> <a href = "http://www.deeplearningbook.org/">Deep Learning</a>, by Ian Goodfellow and Yoshua Bengio and Aaron Courville (freely downloadable!)
</ul>
<h3><font color = "#777777">Tutorials and other useful resources</font></h3>
<ul>
<li> <a href="http://tylerneylon.com/a/learn-lua/">Learn Lua in 15 minutes</a></li>
<li> <a href="https://github.com/torch/torch7/blob/master/doc/tensor.md">Torch's Tensor class</a></li>
<li> <a href="https://github.com/torch/torch7/blob/master/doc/maths.md">Torch's math library</a></li>
</ul>
<h3><font color = "#777777">Latest in deep learning</font></h3>
<ul>
<li> <a href="https://github.com/terryum/awesome-deep-learning-papers">Awesome deep learning papers</a></li>
</ul><HR>
<h2 id = "schedule">Lecture Schedule: </h2>
<br>
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<table cellpadding = "10" border = "1" width = "1000">
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<td> <b><h3><font color = "white">Date</font></h3></b></td>
<td> <b><h3><font color = "white">Content of the Lecture</font></h3></b></td>
<td> <b><h3><font color = "white">Assignments/Readings/Notes</font></h3></b></td>
<td><b><h3><font color = "white">Interesting Extra Readings (not for exam)</font></h3></b></td>
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<tr>
<td>17th March</td>
<td>
<ul>
<li>Concept of pinhole camera, need for pinhole, geometry of perspective projection through pinhole camera
<li>Weak perspective projection and orthographic projection
<li>Concept of image coordinate system and camera coordinate system; intrinsic camera parameters
<li>Concept of world coordinate system and its relationship to camera and image coordinate systems; extrinsic camera parameters
<li>Concept of camera calibration and basic aim of camera calibration
</ul>
</td>
<td><a href = "CameraGeometry.pdf">Slides</a></td>
<td>
<ul>
<li><a href = "http://www1.cs.columbia.edu/CAVE/publications/pdfs/Watanabe_IUW96.pdf">Telecentric lenses: image-space</a>
<li><a href = "http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=817294">Telecentric lenses: object-space</a>
</ul>
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