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Given two times observations , we formulate fine-grained change detection as a joint optimization problem of three related factors , i.e. , normal-aware lighting difference , camera geometry correction flow , and real scene change mask .
 used for: joint optimization problem, fine-grained change detection; feature of: factors, joint optimization problem; hyponym of: normal-aware lighting difference, factors; conjunction: normal-aware lighting difference, camera geometry correction flow; hyponym of: camera geometry correction flow, factors; conjunction: camera geometry correction flow, real scene change mask; hyponym of: real scene change mask, factors
Given options, please tell me the relationships of all the listed entity pairs.Output format is "relation1: word1, word2; relation2: word3, word4". 
Option: conjunction, feature of, hyponym of, used for, part of, compare, evaluate for 
Text: {0} 
 Entity Pairs:  joint optimization problem, fine-grained change detection; factors, joint optimization problem; normal-aware lighting difference, factors; normal-aware lighting difference, camera geometry correction flow; camera geometry correction flow, factors; camera geometry correction flow, real scene change mask; real scene change mask, factors 
Answer:
 used for: joint optimization problem, fine-grained change detection; feature of: factors, joint optimization problem; hyponym of: normal-aware lighting difference, factors; conjunction: normal-aware lighting difference, camera geometry correction flow; hyponym of: camera geometry correction flow, factors; conjunction: camera geometry correction flow, real scene change mask; hyponym of: real scene change mask, factors