Accuracy breakthroughs in mode-specific normalization techniques
The Modality-specific Normalization technology at the core of the MNVTON project redefines the accuracy standard of virtual fitting. The technology realizes fine-grained level of fitting effect control by establishing a triple modality analysis framework of clothing attributes, human body features and environmental elements. At the technical implementation level, the system performs a multimodal decomposition of the input fitting request: the clothing modality focuses on texture preservation and physical simulation, the human body modality focuses on posture adaptation and body shape matching, and the environment modality handles light fusion and background coordination.
Test data shows that this modality-separated processing enables the simulation of garment folds with an accuracy of 921 TP3T, far exceeding the 681 TP3T of the traditional single-modality approach. especially when dealing with complex materials such as silk, the modality-specific normalization algorithm is able to maintain more than 831 TP3T of texture details, whereas the general-purpose normalization method only retains about 551 TP3T of features. Comparison cases provided by the project prove that the technology can control the fit error in key areas such as necklines and cuffs within 3 pixels, which meets the accuracy requirements of commercial application level.
This answer comes from the article1-2-1-MNVTON: Efficient images, virtual trying on of clothes by people in videos (to be opened)The
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