Lecture: Markov Random Fields for Vision and Graphics
Course
- Lecturer(s):
- Start: 19.04.2016
- Dates: Tues. 10:30 (s.t.) - 12:00, LBH / VR Lab I.80
- Course number: MA-INF 2117
- Curriculum: Master
- Effort: 6 CP
- Exams: 26.07.2016, 10:30-12:00 at LBH I.42
Exercises
- Tutor(s):
- Start: 28.04.2016
- Dates: Thurs. 10:30 (s.t.) - 12:00, LBH / VR Lab I.80
Description
This course addresses advanced topics for Markov Random Fields and their use in applications for vision and graphics. We will cover advanced topics in inference and learning such as loopy belief propagation, MCMC sampling, graph cuts and move-making algorithms, dual decomposition and structured learning. Applications discussed will include low and mid-level vision and graphics concepts such as optical flow and stereo depth, super-resolution, superpixels, texture synthesis, segmentation as well as higher-level concepts such as semantic segmentation and object detection. It is recommended but not required to have taken Probabilistic Graphical Models (MA-INF 4315) as a pre-requisite for this course. Those who have not taken Probabilistic Graphical Models should be comfortable with concepts in probability theory and optimization.
News
Due to Pentecost week, there will be no lecture on May 17; the exercise on May 19 for presenting solutions to the coding assignment is shifted to June 2.
Slides
- 01 Intro 190416 (PDF document, 10.0 MB)
- 02 LoopyBeliefProp 260416 (PDF document, 0.9 MB)
- 03 SuperresTexture 020516 (PDF document, 17.6 MB)
- 04 GraphCuts 090516 (PDF document, 3.2 MB)
- 05 ForegroundSeg 240516 (PDF document, 12.3 MB)
- 06 MoveMaking 300516 (PDF document, 1.0 MB)
- 07 DualDecomp 070616 (PDF document, 2.1 MB)
- 08 StereoOpticFlow 140616 (PDF document, 3.3 MB)
- 09 CRFs 210616 (PDF document, 1.2 MB)
- 10 SemanticSeg 280616 (PDF document, 19.9 MB)
- 11 PartModels 050716 (PDF document, 31 MB)
- 12 StructuredLearning 120716 (PDF document, 62 KB)
- 13 DPMobject 190716 (PDF document, 49 KB)
Additional Documents
- 00 MRF2016 CourseInfo (PDF document, 45 KB)
- 01 KollerReadings (PDF document, 1.1 MB)
- 02 HigherOrderModels (PDF document, 2.8 MB)
- 03 StereoIntro (PDF document, 9.6 MB)
- 04 OpticFlowIntro (PDF document, 1.1 MB)
- 05 StructLearningShort (PDF document, 14.5 MB)
- 06 DPM (PDF document, 23 MB)
Assignment Sheets
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Exercise 1: Exercise01 Assignment sheet (PDF document, 115 KB) |
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Exercise 2: Exercise02 Assignment sheet (PDF document, 178 KB)
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Exercise 3: Exercise03 Assignment sheet (PDF document, 170 KB)
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Exercise 4: Exercise04 Assignment sheet (PDF document, 158 KB)
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