OBJECT DETECTION USING VISUAL LANGUAGE MODELS VIA LATENT FEATURE ADAPTATION WITH SYNTHETIC DATA

Abstract: systems and techniques are described herein for adapting a pretrained machine learning model. for instance, a process can include encoding a training image into a first feature vector, the training image including a first object located at a first location; generating a second feature vector based on a set of sinusoidal functions using a set of weights; combining the first feature vector with a second feature vector to generate a combined feature vector; processing the combined feature vector using a visual language model to obtain a second location for the first object; and adjusting the set of weights based on a comparison between the first location and the second location.

Inventor(s): Michael DORKENWALD, Yuki ASANO

CPC Classification: G06V10/86 (IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING)

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