Abstract: A vehicular three-dimensional head-up display includes a display device functioning as a light source; and a combiner for simultaneously reflecting light from the light source toward a driver's seat and transmitting light from the outside of a vehicle, and may include an optical configuration in which an image created by the light from the light source is displayed as a virtual image of a three-dimensional perspective laid to correspond to the ground in front of the vehicle.

Abstract: A method for extracting a fingerprint of a video includes calculating 2D discrete cosine transform (DCT) coefficients from each of the plurality of frames of the video, extracting, from the 2D DCT coefficients, a coefficient having a basis satisfying at least one of up-down symmetry or left-right symmetry, and calculating a fingerprint of the video based on the extracted coefficient.

Abstract: A navigating robot includes: a feature module configured to detect objects in images captured by a camera of the navigating robot while the navigating robot is in a real world space; a mapping module configured to generate a map including locations of objects captured in the images and at least one attribute of the objects; and a navigation module trained to find and navigate to N different objects in the real world space in a predetermined order by: when a location of a next one of the N different objects in the predetermined order is stored in the map, navigate toward the next one of the N different objects in the real world space; and when the location of the next one of the N different objects in the predetermined order is not stored in the map, navigate to a portion of the map not yet captured in any images.

Abstract: A system includes: a first module configured to, based on a set of target robot joint angles, generate a first estimated end effector pose and a first estimated latent variable that is a first intermediate variable between the set of target robot joint angles and the first estimated end effector pose; a second module configured to determine a set of estimated robot joint angles based on the first estimated latent variable and a target end effector pose; a third module configured to determine joint probabilities for the robot based on the first estimated latent variable and the target end effector pose; and a fourth module configured to, based on the set of estimated robot joint angles, determine a second estimated end effector pose and a second estimated latent variable that is a second intermediate variable between the set of estimated robot joint angles and the second estimated end effector pose.

Abstract: A system includes: a feature module configured to generate a feature map based on a single image taken from a point of view (POV) including a human based on features of the human visible in the image and non-visible features of the human; a pixel features module configured to generate pixel features based on the feature map and a target POV; a feature mesh module configured to generate a feature mesh for the human based on the feature map; a geometry module configured to: generate voxel features based on the feature mesh; and generate a density value based on the voxel and pixel features; a texture module configured to generate RGB colors for pixels based on the density value and the pixel features; and a rendering module configured to generate a three dimensional rendering of the human from the target POV based on the RGB colors and the density value.

Abstract: A method for generating a language model for text generation by receiving a pre-trained language model having attributes with existing probability distributions over the pre-trained language model; receiving at least one target constraint; the target constraint specifying an expectation of a target attribute over a language model that approximates the pre-trained language model; computing parameters of an energy based model by applying the target constraint to the pre-trained language model; obtaining samples from a reference policy; updating parameters of a target policy using the obtained samples and the energy based model; updating the reference policy with the target policy if the target policy is superior to the reference policy; and outputting the target policy as a target language model. The target language model is adapted to generate text with the target attribute over a probability distribution that approximates the desired probability distribution specified by the target constraint.

Abstract: A method for providing an optimal path through a computer network includes predicting a subsequent action of a target user through an optimal path prediction model that is trained in a form of a graph representing a user action trajectory of a session unit and recommending a path of the predicted action as an optimal path. The recommendation includes identifying a user intent based on a previous action trajectory of the target user in a current session, and guiding a path corresponding to the user intent as one of the optimal paths.

Abstract: An audio recording management method includes creating a text transcript of an audio recording by converting speech to text, matching and managing the text transcript and a memo written during recording or playback of the audio, and providing the text transcript in connection with the memo.

Abstract: A method for managing data center failures, executed by one or more processors of a leader management node, includes allocating a first data node among a first plurality of data nodes a master data node, the first plurality of data nodes being in a first data center, allocating a second data node among the first plurality of data nodes as a first backup data node, allocating one among a second plurality of data nodes as a second backup data node, the second plurality of data nodes being in a second data center, and the first data center and the second data center being located in different regions, and setting a data replication mode between the master data node, the first backup data node and the second backup data node, the data replication mode being selected from a set of modes including a first mode and a second mode.

Abstract: An image synthesis method includes inputting an original image and a watermark image into a synthesis model and obtaining a synthesized image output from the synthesis model. The original image and the watermark image are respectively processed in first and second sub-models of the synthesis model and then combined, and the concatenated result is processed in a third sub-model to generate the synthesized image.

Abstract: A generative adversarial network, a method of training a generator neural network, and a method of generating images using the generator network is provided. The generator neural network is configured to process an input comprising a noise vector and a pair of conditioning variables to generate an image according to the conditioning variables. The generator neural network includes a mixed-conditional batch normalization layer. The mixed-conditional batch normalization layer is configured to normalize a network layer output to generate a normalized network layer output, comprising transforming the network layer output in accordance with mixed-conditional batch normalization layer parameters to generate the normalized network layer output, wherein the mixed-conditional batch normalization layer parameters are computed by applying an affine transformation to the conditioning variables.

Abstract: A system includes: a training dataset including first objects of a first modality and second objects of a second modality different than the first modality, where the second objects include text that is descriptive of the first objects; a first matrix including first relevance values indicative of relevance between the first objects and the second objects, respectively; a second matrix including second relevance values indicative of relevance between the second objects and the first objects, respectively; and a training module configured to: assign ones of the second objects to bins based on distances between the ones of the objects and a query; determine a ranking measure based on a number of the ones of the second objects assigned to the bins; determine losses based on the ranking measure and the first and second matrices; determine a final loss based on the losses; train embedding functions based on the final loss.

Abstract: A confidence estimation system includes: a neural network including at least one an attention module including N heads configured to: generate attention matrices based on interactions between tokens for words in an input sequence of words, the input sequence of words including a word that is obscured; and determine the word that is obscured in the input sequence; and a confidence module configured to determine a confidence value indicative of a probability of the neural network correctly determining the word that is obscured, the confidence module determining the confidence value of the word that is obscured using a convolutional neural network that projects the attention matrices generated by the attention module over a multi-dimensional space, the attention matrices recording interactions between the tokens in the input sequence of words without information regarding the tokens for the words and the word that is obscured.

Abstract: A method extends the Trip Based Public Transit Routing algorithm to compute personalized itineraries in a multimodal network based on custom transfer speed and maximum transfer duration. The customization is done at query time. The method modifies the pruning phase and the search phase of the Trip Based Public Transit Routing algorithm to obtain Pareto front for minimizing arrival time and number of transfers, along with one optimal solution per value in the Pareto front.

Abstract: In a mechanical system with an object having a set of two or more contacts, methods are disclosed for determining object motion by computing the tangential generalized reaction impulse and force. The methods includes receiving input values that include an initial generalized position and an initial generalized velocity of the object at time t, and computing a generalized force. The methods further includes computing, respectively for the reaction impulse and force: a generalized reaction impulse and force, and a tangential generalized reaction impulse and force. The methods use the tangential generalized reaction impulse and force to, respectively, compute an end-of-interval generalized position and velocity, and a generalized acceleration, which are output for use by an application.

Abstract: A method for processing an audio signal includes setting target loudness; receiving metadata of an audio signal from a server; and adjusting the loudness of the audio signal by using the received metadata, so that the loudness of the audio signal corresponds to the set target loudness.

Abstract: Security check methods and systems over a user on a vehicle may be provided. The security check method including checking an allowed security right to a destination of a vehicle for entry, detecting a security right of a user on the vehicle, and performing a security process related to getting off the vehicle, based on the security right of the user and the allowed security right may be provided.

Abstract: A gravity compensation assembly including a main frame having one side connected to a weight body to be supported, and the other side where an inner rotation portion and an outer rotation portion spaced apart from each other and having rotation axis in an x-axis direction are coupled, an auxiliary frame having one side rotatably connected to the inner rotation portion of the main frame, and the other side where an auxiliary rotation portion having a rotation axis in the x-axis direction is coupled, and an elastic force providing having one side rotatably connected to the outer rotation portion of the main frame, and the other side coupled to the auxiliary rotation portion of the auxiliary frame, and configured to perform load compensation by an elastic force when a center of gravity changes as a relative angle of the main frame and the auxiliary frame changes may be provided.

Abstract: In a method for generating a normalized sequential model using a processor, a sequential energy-based model computed by a parameterized neural network is provided. The sequential energy-based model defines an unnormalized probability distribution over a target sequence for a context source. The normalized sequential model is generated by projecting the sequential energy-based model onto a target autoregressive model that approximates a normalized distribution associated with the sequential energy-based model.

Abstract: A chatroom providing method includes searching for a consultation product corresponding to a user request; processing payment for the consultation product selected from the result of the search; and providing a one-to-one conversation by activating a chatroom between a user and an expert who has registered the consultation product for which the payment has been completed. A guide information associated with the consultation product is configured and provided in the chatroom as a chatbot message.