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Coupled Dictionary and Feature Space Learning with Applications to Cross-Domain Image Synthesis and Recognition
2013 IEEE International Conference on Computer Vision
Cross-domain image synthesis and recognition are typically considered as two distinct tasks in the areas of computer vision and pattern recognition. Therefore, it is not clear whether approaches addressing one task can be easily generalized or extended for solving the other. In this paper, we propose a unified model for coupled dictionary and feature space learning. The proposed learning model not only observes a common feature space for associating cross-domain image data for recognitiondoi:10.1109/iccv.2013.310 dblp:conf/iccv/HuangW13 fatcat:tqc7zjlierdeldamroqj4zkhhq