Large-Scale Coarse-to-Fine Object Retrieval Ontology and Deep Local Multitask Learning
Table 2
Contributions of CFOR in the online phase and its comparison with DeepFashion [8].
Criteria
Query
Retrieval process
Indexing method
Retrieval results
CFOR system
Image + optional semantic information (categories and attributes) extracted automatically from an image
Conducted by deep networks based on object ontology at three levels: region, category, and attribute levels
Quantized inverted indexing is operated by object ontology
Object ontology supports achieving retrieval results. Retrieval results are based on deep global features and attribute vector. Query expansion is used to improve the performance of the retrieval system.