A system for lightweight multi-branch and multi-scale (LMBMS) re-identification is described herein. The system includes a convolutional neural network trained for person identification, wherein the convolutional neural network comprises a series of residual blocks that obtain input from a head network of the convolutional neural network. The system also includes a plurality of refine blocks, wherein one or more refine blocks take as input features from a residual block of the series of residual blocks, wherein the features are at input at different scales and different resolutions and an output of the plurality of refine blocks is a plurality of features in a same feature space. A channel-wise attention mechanism may merge the plurality of features and generate final dynamic features.