A shape estimating apparatus comprising: an acquiring unit configured to acquire a two-dimensional image ; and an estimating unit that includes artificial intelligence, and is configured to provide the artificial intelligence with the two-dimensional image and cause the artificial intelligence to estimate a three-dimensional shape of a subject of the two-dimensional image , wherein a learning result of machine learning performed using learning data containing supervisor data comprising shape information expressing a three-dimensional shape of a sample subject and a sample two-dimensional image obtained by capturing an image of the three-dimensional shape of the sample subject is set to the artificial intelligence, the estimating unit is configured to cause the artificial intelligence to estimate a three-dimensional shape of the subject of the two-dimensional image , thereby obtaining, from the artificial intelligence, shape information describing the three-dimensional shape, and characterized in that the respective shape information contains, for each deformation that is to be applied to a surface of a predetermined three-dimensional shape expressed by a basic model, positional information and intensity information respectively defining a position and an intensity of the deformation, wherein the respective deformation includes a first type of deformation for displacing a point of action indicated by the positional information on the surface of the predetermined three-dimensional shape, by an amount indicated by the intensity information, along a direction of action that is substantially parallel to a straight line extending from a predetermined origin to the point of action. an acquiring unit configured to acquire a two-dimensional image ; and an estimating unit that includes artificial intelligence, and is configured to provide the artificial intelligence with the two-dimensional image and cause the artificial intelligence to estimate a three-dimensional shape of a subject of the two-dimensional image , wherein a learning result of machine learning performed using learning data containing supervisor data comprising shape information expressing a three-dimensional shape of a sample subject and a sample two-dimensional image obtained by capturing an image of the three-dimensional shape of the sample subject is set to the artificial intelligence, the estimating unit is configured to cause the artificial intelligence to estimate a three-dimensional shape of the subject of the two-dimensional image , thereby obtaining, from the artificial intelligence, shape information describing the three-dimensional shape, and characterized in that the respective shape information contains, for each deformation that is to be applied to a surface of a predetermined three-dimensional shape expressed by a basic model, positional information and intensity information respectively defining a position and an intensity of the deformation, wherein the respective deformation includes a first type of deformation for displacing a point of action indicated by the positional information on the surface of the predetermined three-dimensional shape, by an amount indicated by the intensity information, along a direction of action that is substantially parallel to a straight line extending from a predetermined origin to the point of action. <EOS>