Abstract: A method of image completion comprises: constructing the image repair model and constructing a plurality of conditional generative adversarial networks according to a plurality of object types; inputting the training image corresponding to the plurality of objective types such that the plurality of conditional generative adversarial networks respectively conduct a corruption feature training; inputting the image in need of repair and respectively conducting an image repair through the plurality of conditional generative adversarial networks to generate a plurality of repaired images; and judging a reasonable probability of the plurality of repaired images through a probability analyzer, choosing an accomplished image and outputting the accomplished image through an output interface.

Abstract: An indoor scene structural estimation system and an estimation method based on deep learning network are provided. An indoor scene structural estimation system based on deep learning network includes a 2D encoder, a 2D plane decoder, a 2D edge decoder, a 2D corner decoder, and a 3D encoder. The 2D encoder receives an input image and encodes the input image. The 2D plane decoder is connected to the 2D encoder, decodes the encoded input image, and generates a 2D plane segment layout image. The 2D plane decoder is connected to the 2D encoder, decodes the encoded input image, and generates a 2D plane segment layout image. The 2D corner decoder is connected to 2D encoder, decodes the encoded input image, and generates a 2D corner layout image.

Abstract: An indoor scene structural estimation system and an estimation method based on deep learning network are provided. An indoor scene structural estimation system based on deep learning network includes a 2D encoder, a 2D plane decoder, a 2D edge decoder, a 2D corner decoder, and a 3D encoder. The 2D encoder receives an input image and encodes the input image. The 2D plane decoder is connected to the 2D encoder, decodes the encoded input image, and generates a 2D plane segment layout image. The 2D plane decoder is connected to the 2D encoder, decodes the encoded input image, and generates a 2D plane segment layout image. The 2D corner decoder is connected to 2D encoder, decodes the encoded input image, and generates a 2D corner layout image.

Abstract: A method of image completion comprises: constructing the image repair model and constructing a plurality of conditional generative adversarial networks according to a plurality of object types; inputting the training image corresponding to the plurality of objective types such that the plurality of conditional generative adversarial networks respectively conduct a corruption feature training; inputting the image in need of repair and respectively conducting an image repair through the plurality of conditional generative adversarial networks to generate a plurality of repaired images; and judging a reasonable probability of the plurality of repaired images through a probability analyzer, choosing an accomplished image and outputting the accomplished image through an output interface.