Abstract.We present an end-to-end solution for recognizing merchan- dise displayed in the shelves of a supermarket.Given images of individual products,which are taken under ideal illumination for product market- ing,the challenge is to find these products automatically in the images of the shelves.Note that the images of shelves are taken using hand-held camera under store level illumin ation.We provide a two-layer hypotheses generation and verification model.In the first layer,the model predicts a set of can didate merchandise at a specific location of the shelf while in the second layer,the hypothesis is verified by a novel graph theoretic approach.The perform ance of the proposed approach on two publicly available datasets is better than the competing approaches by at least 10%.