This course covers several fundamental and interesting topics in computational photography and computer
vision, such as colorization,
texture synthesis, inpainting, HDR imaging, tone mapping, deblurring, stabilization, super-resolution, matting,
warping, matchmoving,
and so on. Students are expected to learn the selected topics, know how they can be used to create visual
effects in images and
videos, and acquire hands-on experience of related techniques.

Computer Vision for Visual Effects, Richard J. Radke, Cambridge University Press,

Computer Vision: Algorithms and Applications, Richard Szeliski, 2010

Teaching Method
3-hour lectures and discussions every week
All assignments, readings, and projects are done in groups.
Each group contains 2-3 students.

1 introduction, image formation, color, color harmonization, color grading
2 colorization, chrominance blending
3 texture synthesis, image analogies
4 inpainting, seam carving, internet-based inpainting, sparse coding
5 HDR imaging, tone mapping
6 bilateral filtering, nonlocal means, joint bilateral filtering
7 gradient domain compression, HDR related
8 intrinsic images, relighting
9 graphical models
10 matting
11 poisson image editing, patch-based editing
12 warping and morphing, rigid morphing
13 faces
14 features and matching
15 matching and dense correspondences
16 dense correspondences
17 matchmoving
18 term project poster

85% assignments, readings, and projects
15%: participation

Course website