A Fair Comparison Should be Based on the Same Protocol -- Comments on "Trainable Convolution Filters and Their Application to Face Recognition"
Liang Chen , Wenzhou University, China and University of Northern British Columbia, BC
We comment on a paper describing an image classification approach called Volterra kernel classifier, which was called Volterrafaces when applied to face recognition. The performances were evaluated by the experiments on face recognition databases. We find that their comparisons with the state of the art of three databases were indeed based on unfair settings. The results with the settings of the standard Protocol on three datasets are generated, which show that Volterrafaces achieves the state of the art performances only in one database.
Protocols, Standards, Face recognition, Kernel, Computer vision, Training, Miscellaneous, Classifier design and evaluation, Computer vision
L. Chen, "A Fair Comparison Should be Based on the Same Protocol -- Comments on "Trainable Convolution Filters and Their Application to Face Recognition"," in IEEE Transactions on Pattern Analysis & Machine Intelligence.