Abstract: A computer-implemented method for generating an image involves receiving input text and layout information, decomposing the text into global and local features, and encoding these features into vectors. The method initializes an initial image representation and uses a trained neural network to predict global noise from the global vector and initial image representation. It also predicts initial local noise for each local feature using their respective vectors and the initial image representation. The final local noise for each feature is determined using the initial local noise and the global noise. The predicted global and final local noises are combined based on the layout information. Finally, the initial image representation is denoised using this combined noise to produce the next image representation, ultimately generating the image.

Abstract: A computer-implemented method comprising: based on an input scene graph, generating a plurality of graph vectors; encoding an input image to generate a plurality of image vectors; performing an update process to generate a plurality of updated graph vectors and at least one updated object query vector, comprising: updating the at least one object query vector based on the plurality of graph vectors; updating the at least one object query vector based on the plurality of image vectors; and updating the plurality of graph vectors based on the at least one object query vector; extracting from the at least one updated object query vector a region and a category of the at least one object; and computing a matching score indicating a similarity between the input image and the input scene graph based on the at least one updated object query vector and the plurality of updated graph vectors.

Abstract: A non-transitory computer-readable recording medium storing a machine learning program causing a computer to execute a process including: generating vector information based on a first feature of a target included in an image, a second feature of the target, and conversion parameters; and executing training of a machine learning model and update of the conversion parameters by inputting the image and the vector information to the machine learning model, the machine learning model including a first machine learning model portion configured to identify the first feature and a second machine learning model portion configured to identify the second feature.

Abstract: A recording medium storing a program for causing a computer to execute processing including: acquiring, from a first model trained based on training data in which the first object is labeled in an image, a first portion specifying a region in an image that includes a first object; generating a third model by combining the first portion and a third portion of a second model being a model that includes a second portion and the third portion and that is trained based on training data in which position information regarding the second object is labeled in an image, the second portion being a portion that specifies a region in an image including a second object, the third portion being a portion that determines a position in an image of a specified region; and outputting a detection result of an object by inputting an image to the third model.

Abstract: A non-transitory computer-readable storage medium storing an information processing program that causes at least one computer to execute a process, the process includes receiving, from a server, a plurality of pieces of first feature data that correspond to each of a plurality of pieces of image data; acquiring text data included in search conditions, the search conditions being transmitted from a client device; receiving second feature data that corresponds to the text data and is transmitted from the server, in response to transmitting the text data to the server; and acquiring a plurality of degrees of similarity between the plurality of pieces of the first feature data and the second feature data.

Abstract: An object detection device includes a processor that executes a procedure. The procedure includes: converting an input image into a first vector such that information related to an area of an object in the image is contained in the first vector; converting input text into a second vector such that information related to an order of appearance in the text of one or more word strings each indicating a detection target object included in the text is contained in the second vector; generating a third vector in which the first vector and the second vector have been reflected in a vector of initial values corresponding to detection target objects; and estimating whether or not a feature indicated by the third vector corresponds to a detection target object that appears at which number place in the text, and estimating a position of the detection target object in the image.

Abstract: A storage medium storing a machine learning program that causes a computer to execute a process that includes generating a feature of a training image by inputting the training image to a first model; generating text corresponding to the training image by inputting first training text to the first model; generating a feature of second training text, for which a correct answer as to whether the second training text corresponds to the training image is known, by inputting the second training text to a second model; and changing a parameter of the first model and a parameter of the second model so that a first error between the first training text and the generated text corresponding to the training image and a second error between the correct answer and a degree of similarity between the feature of the training image and the feature of the second training text decrease.

Abstract: A method includes: correcting a vector of a first modal by using a correlation between the vector of the first modal and a vector of a second modal different from the first modal; correcting the vector of the second modal by using the correlation between the vector of the first modal and the vector of the second modal; generating a first vector by using a correlation of two different types of vectors obtained from the corrected vector of the first modal; generating a second vector by using the correlation of the two different types of vectors obtained from the corrected vector of the second modal; generating a third vector in which the first and second vectors are aggregated by using the correlation of the two different types of vectors obtained from a combined vector including a predetermined vector, the generated first and second vectors; and outputting the generated third vector.

Abstract: A computer-implemented outputting method including: generating a correction vector that corrects a vector based on information of a first modal on the basis of correlation between the vector based on the information of the first modal and a vector based on information of a second modal; combining the generated correction vector with the vector based on the information of the first modal; compressing the combined vector based on the information of the first modal according to a predetermined rule; performing normalization processing for the compressed vector based on the information of the first modal; and outputting a vector obtained by the normalization processing.

Abstract: A non-transitory computer-readable storage medium storing a determination model generation program that causes at least one computer to execute a process, the process includes generating, based on first training data in which image data and character string data that corresponds to the image data are associated with each other, second training data by replacing one of data included in the first training data selected from the image data and the character string data with another data; and generating, by using the first training data and the second training data as input data, a determination model that outputs information that indicates which training data selected from the first training data and the second training data is training data in which correspondence between the image data and the character string data is correct.

Abstract: A non-transitory computer-readable storage medium storing a machine learning program for causing a computer to execute a process includes acquiring a plurality of vectors that indicate a feature of each of a plurality of partial images extracted from an image; calculating a same number of vectors as a certain number of vectors based on the plurality of vectors and the certain number of vectors; and changing parameters of a neural network by executing machine learning based on vectors that indicate a feature of text and the same number of vectors.

Abstract: A device for estimating a degree of freedom for movement includes a memory, and a processor coupled to the memory and the processor configured to acquire first three-dimensional information of a target object at a first time and second three-dimensional information of the target object at a second time, specify a movable portion of the target object according to a difference between the first three-dimensional information and the second three-dimensional information, estimate the degree of freedom for movement of the movable portion included in the target object according to displacement of the movable portion between the first three-dimensional information and the second three-dimensional information, and assign degree of freedom information for indicating the degree of freedom for movement to a three-dimensional model for representing the target object, based on the estimated degree of freedom for movement of the movable portion.

Abstract: A flying device configured to communicate with a controller device operated by a user, the flying device includes: a memory; and a processor coupled to the memory and configured to: determine whether the flying device is in contact with an object based on a signal from a contact detector; and move the flying device in a direction corresponding to an operation command transmitted from the controller device while causing a thrust force to be produced so that a contact between the object and the flying device is maintained when it is determined that the flying device is in contact with the object.

Abstract: A flying machine includes: a flying machine body that includes a rotor blade; a protective member that forms a frame shape inside which the rotor blade is disposed, that is rotatably fixed to both end portions of the flying machine body, and that is pipe shaped; and a connecting wire that passes through an inner portion of the protective member to connect the flying machine body and an external device together.

Abstract: A non-transitory computer-readable recording medium stores therein an information processing program that causes a computer to execute a process including: acquiring images photographed with a first angle of view and a second angle of view wider than the first angle of view; specifying a position and an attitude of a camera that photographed the image photographed with the first angle of view based on the image photographed with the second angle of view; stitching a plurality of images photographed with the first angle of view to generate a panoramic image; correcting the position on the generated panoramic image, of the image photographed with the first angle of view based on the specified position and attitude of the camera; and mapping the panoramic image to a three-dimensional model by texture mapping based on the corrected position.

Abstract: A flying machine includes a flying machine body including a rotor blade; a frame including a frame body supporting the flying machine body, and a pressing section that is pressed against a target object at least at two locations separated along a direction orthogonal to a width direction of the frame body; and a detector fixed to the frame, and having a detection direction that is a direction orthogonal to a direction joining the two locations together and facing toward the target object.

Abstract: A flying machine frame structural body including: a frame that surrounds a flying machine body including a rotating blade, and to which the flying machine body is fixed; and plural wheels that are rotatably supported by the frame.

Abstract: A device for estimating a degree of freedom for movement includes a memory, and a processor coupled to the memory and the processor configured to acquire first three-dimensional information of a target object at a first time and second three-dimensional information of the target object at a second time, specify a movable portion of the target object according to a difference between the first three-dimensional information and the second three-dimensional information, estimate the degree of freedom for movement of the movable portion included in the target object according to displacement of the movable portion between the first three-dimensional information and the second three-dimensional information, and assign degree of freedom information for indicating the degree of freedom for movement to a three-dimensional model for representing the target object, based on the estimated degree of freedom for movement of the movable portion.

Abstract: An information providing method includes: measuring a static object three-dimensionally in an environment, by a processor; sequentially measuring a position of a dynamic object in the environment, by the processor; transmitting measurement data of the static object measured to a predetermined information processing apparatus through a communication network; transmitting measurement data of the dynamic object measured to the information processing apparatus through a communication network; receiving support data rem the information processing apparatus based on an environment grasping image that is generated from the measurement data, of the static object and the measurement data of the dynamic object by the information processing apparatus; and presenting the received support data to the environment at predetermined timing, by the processor.

Abstract: A flying device configured to communicate with a controller device operated by a user, the flying device includes: a memory; and a processor coupled to the memory and configured to: determine whether the flying device is in contact with an object based on a signal from a contact detector; and move the flying device in a direction corresponding to an operation command transmitted from the controller device while causing a thrust force to be produced so that a contact between the object and the flying device is maintained when it is determined that the flying device is in contact with the object.