The present application relates to the technical field of virtual clothing recommendation, and specifically discloses a virtual clothing fitting recommendation method and
system based on
artificial intelligence, which establishes a cross-domain feature decoupling and alignment mechanism by fusing commodity standard images and user real-shot images, realizes the extraction and unified representation of the essential visual attributes of clothing, and fundamentally solves the problem of inconsistent clothing appearance caused by differences in shooting conditions. By constructing an environment-independent
feature model and
a domain-
invariant feature space, the
system can accurately measure the visual similarity of clothing in images from different sources, significantly improving the reliability and user trust of the recommendation results. The
system realizes precise matching of the recommendation results and high-fidelity presentation of the virtual fitting effect, can accurately capture the fitting effect of clothing and individual form before the user makes a purchase decision, and realizes early identification and visual satisfaction of personalized needs.