SYSTEMS AND METHODS FOR TRAINING MODELS TO PREDICT DENSE CORRESPONDENCES IN IMAGES USING GEODESIC DISTANCES

SYSTEMS AND METHODS FOR TRAINING MODELS TO PREDICT DENSE CORRESPONDENCES IN IMAGES USING GEODESIC DISTANCES

Systems and methods for training models to predict dense correspondences across images such as human images. A model may be trained using synthetic training data created from one or more 3D computer models of a subject. In addition, one or more geodesic distances derived from the surfaces of one or...

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Bibliographische Detailangaben
Hauptverfasser: SUN, Deqing, GUO, Kaiwen, BOUAZIZ, Sofien, TANG, Danhang, TAN, Feitong, FANELLO, Sean Ryan Francesco, KESKIN, Cem, PANDEY, Rohit Kumar, DU, Ruofei, DOU, Mingsong, ZHANG, Yinda
Format: Patent
Sprache:eng ; fre ; ger
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
PHYSICS
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Beschreibung
Zusammenfassung:Systems and methods for training models to predict dense correspondences across images such as human images. A model may be trained using synthetic training data created from one or more 3D computer models of a subject. In addition, one or more geodesic distances derived from the surfaces of one or more of the 3D models may be used to generate one or more loss values, which may in turn be used in modifying the model's parameters during training.