Part-based annotation-free fine-grained classification of images of retail products

Bikash Santra, Avishek Shaw, Dipti Prasad Mukherjee

Abstract: Highlights•A deep convolutional reconstruction-classification network,RC-Net is introduced for fine-grained classification of products.•An annotation-free conv-LSTM based part-level classifier is proposed to classify discriminative parts of the products.•The discriminative parts of the products are identified in a unique unsupervised technique.•Proposed fine-grained classifier significantly improves the performance of R-CNN for detecting retail products.