2. MRFs
(X1,X2) 1 2 3 X3 X1 X2 4
(X2,X3,X3) X4

3. CRFs
Image I
(X1,X2,I) 1 2 3 X3 X1 X2 4
(X2,X3,X3,I) X4

4. Examples X = Image patches X = Patches on a regular lattice
[Quattoni et al.]
MRF
CRF
X = Patches on a regular lattice
[Kumar]

5. Examples
X = pixels, regions, image
[He et al.]

6. Issues Inference Learning Easy only when the planets are aligned
Approximate solutions only  How good are they?
Learning
Difficult and slow
Limits the complexity of the models

7. Issues Generality Global label inference
Can use arbitrary models but limited to restricted models in practice because of inference and learning challenges
Global label inference
Inference over global labeling of the data in theory, but limited propagation across image in practice
Support limited by the complexity of learning and inference
Use of complex graph and clique structure is difficult