Abstract: A method of performing image retrieval includes: obtaining a query image; generating a global feature descriptor of the query image by inputting the query image into a convolutional neural network (CNN) and obtaining the global feature descriptor as an output of the CNN, where parameters of the CNN are learned during training of the CNN on a batch of training images using a listwise ranking loss function and optimizing a quantized mean average precision ranking evaluation metric; determining similarities between the query image and other images based on distances between the global feature descriptor of the query image and global feature descriptors of the other images, respectively; ranking the other images based on the similarities, respectively; and selecting a set of the other images based on the similarities between the query image and the other images.

Abstract: Electronic devices and/or operating methods of the electronic device to provide visual localization based on outdoor three-dimensional (3D) map information may be provided. Such electronic devices may be configured to acquire two-dimensional (2D) image information about an outdoor environment, generate 3D map information about the outdoor environment based on the 2D image information, and determine a position of a point in the 3D map information corresponding to a query image.

Abstract: A method preprocesses a set of non-scheduled lines within a multimodal transportation network of predetermined stations, by (a) for each non-scheduled line (l) of the set of non-scheduled lines, associating, to each station (plj) of a sequence of stations ({right arrow over (p)}(l)) defining the non-scheduled line (l), at least one time interval (I(l,j)) during which a trip on the non-scheduled line (l) can depart from the station (plj); (b) for each first station (plj) of a non-scheduled line (l) which is reachable from a second station (pti) of a scheduled line, adding to a set of feasible transfers between a scheduled line and a non-scheduled line, if there exists a trip (t) on the scheduled line such that a departure time at the first station (plj) after transferring is compatible with the at least one time interval (I(l,j)) associated to the first station (plj), the earliest transfer from the second station (pti) on the trip (t) to the first station (plj); and (c) outputting the set of feasible transfers

Abstract: A system for generating whole body poses includes: a body regression module configured to generate a first pose of a body of an animal in an input image by regressing from a stored body anchor pose; a face regression module configured to generate a second pose of a face of the animal in the input image by regressing from a stored face anchor pose; an extremity regression module configured to generate a third pose of an extremity of the animal in the input image by regressing from a stored extremity anchor pose; and a pose module configured to generate a whole body pose of the animal in the input image based on the first pose, the second pose, and the third pose.

Abstract: A pre-trained source encoder generates a source encoder representation for each image of a labeled set of source images from a source domain. A target encoder generates a target encoder representation for each image of an unlabeled set of target images from a target domain. A generative adversarial network outputs a first prediction indicating whether each of the source encoder representations and each of the target encoder representations originate from the source domain or the target domain. The generative adversarial network outputs a second prediction of the latent code for each of the source encoder representations and each of the target encoder representations. The target encoder and the generative adversarial network are trained by repeatedly updating parameters of the target encoder and the generative adversarial network until one or more predetermined stopping conditions occur.

Abstract: A multi-document summarization system includes: an encoding module configured to receive multiple documents associated with a subject and to, using a first model, generate vector representations for sentences, respectively, of the documents; a grouping module configured to group first and second ones of the sentences associated with first and second aspects into first and second groups, respectively; a group representation module configured to generate a first vector representation based on the first ones of the sentences and a second vector representation based on the second ones of the sentences; a summary module configured to: using a second model: generate a first sentence regarding the first aspect based on the first vector representation; and generate a second sentence regarding the second aspect based on the second vector representation; and store a summary including the first and second sentences in memory in association with the subject.

Abstract: A method for operating a user terminal providing a video slide service includes uploading a UGC video to a server; receiving, from the server, scene metadata information for each reproduction section corresponding to the UGC video; generating a video slide file based on the scene metadata information for each reproduction section; displaying an item corresponding to the video slide file; and displaying a page screen composed of representative image information and subtitle information, for each reproduction section of the UGC video in response to a user selection on the item.

Abstract: A method and a system for conference assistance provide, as a conference assistance tool, a screen including an original text that is a text input in one of a plurality of languages set to be used in a conference and a translation text that is translated from the original text in another language.

Abstract: A comment processing method may include specifying a desired section in content that includes at least one of a text and an image in response to a selection of a user, and registering a comment input from the user to the specified section; and highlighting the section to which the comment is registered in the content, and displaying at least one comment among comments registered to the highlighted section at a point in time at which the highlighted section is displayed on a screen area.

Abstract: A method includes: selecting a set of access points in a focus zone that identifies an area around the travel destination; determining access paths through one or more access points in the set of selected access points; listing crossings that the access paths pass through; for each of the listed crossings: determining a probability that the listed crossing is passed through by an access path; determining at least one complexity score of the listed crossing; determining a set of points of interest (POIs) along access paths passing through the listed crossing; and determining quality scores for the POIs, respectively, the quality score of one of the POIs reflecting a utility of that one of the POIs to facilitate orientation; selecting POIs from the set of POIs based on the quality scores; generating the access map including the access paths and the selected POIs; and outputting the access map.

Abstract: A multiple sound source mixing method includes dividing a plurality of sound source data into segments each with a desired length; sequentially inputting sound source data of a corresponding segment for each segment through a desired number of nodes with respect to the plurality of sound source data and mixing the input sound source data into a single piece of sound source data; and concatenating the sound source data mixed for the respective segments.

Abstract: Disclosed are an electronic apparatus for recognizing a multimedia signal and an operating method of the electronic apparatus, including segmenting a detection signal into a plurality of frames; segmenting each of the frames into a plurality of blocks; and representing each of the blocks as a hash word based on a time feature and a frequency feature for each of the blocks.

Abstract: There is provided an approach for using street view images, captured from a selected geographical area, to obtain one or more of a landmark saliency score and a street crossing simplicity score, with each score reflecting a degree to which a computer-implemented circuit (including image recognition engines and a visual element matching module) can recognize and identify a landmark in at least one of the street view images. In turn, a navigational plan for a selected geographical area, including travel directions, is generated with the one or more of the landmark saliency score and the street crossing simplicity score.

Abstract: A computer implemented method for multi-document question answering is performed on a server communicating with a client device over a network. The method includes receiving a runtime question from a client device and retrieving runtime documents concerning the runtime question using a search engine. Runtime answer samples are identified in the retrieved runtime documents. A neural network model, trained using distant supervision and distance based ranking loss, is used to compute runtime scores from runtime question data representing the runtime question and from a runtime answer sample representing a first portion of text from the corpus of documents, where each runtime score represents a probability an answer to the runtime question is present in the runtime answer samples. A runtime answer is selected from the runtime answer samples corresponding to the highest runtime score sent to the client device.

Abstract: A method of determining a highlight section of a sound source includes obtaining a sound source and classification information of the sound source, and learning a neural network by using the sound source and the classification information. The neural network includes an input layer including a node corresponding to a feature value of each of a plurality of sections obtained by splitting the sound source according to a time axis, an output layer including a node corresponding to the classification information, a hidden layer defined between the input layer and the output layer, a first function between the input layer and the hidden layer, and a second function between the hidden layer and the output layer, wherein the first function includes an attention model for calculating a weighted sum of the feature value of each section. The highlight section of the sound source is determined based on weight information of a feature value node of each section included in the first function.

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 training system for training a trained model for use by a navigating robot to perform visual navigation includes memory including N base virtual training environments, each of the N base virtual training environments including a field of view at a location within an indoor space, where N is an integer greater than 1. A randomization module is configured to generate N varied virtual training environments based on the N base virtual training environments, respectively, by varying at least one characteristic of the respective N base virtual training environments. A training module is configured to train the trained model for use by the navigating robot to perform visual navigation based on a training set including: the N base virtual training environments; and the N varied virtual training environments.

Abstract: A parallel audio transcoding method includes splitting audio into segments of a certain length; performing parallel transcoding by allocating the split segments to a plurality of encoders; and concatenating the segments encoded through the parallel transcoding and merging the same into a single encoded file. Performing parallel transcoding includes inserting additional regions, which overlap and neighbor each of the split segments, and sending the same to the encoders, and merging includes cutting out the additional regions from the encoded stream to create a stream corresponding to the split segments.

Abstract: A computer-implemented method for training a neural end-to-end aspect based sentiment analysis (ABSA) system includes: inputting a batch of samples of a dataset into the neural end-to-end ABSA system, where the neural end-to-end ABSA system includes: a contextual language encoder configured to embed tokens with context; a first self-attention network configured to, based on an output of the contextual language encoder, detect an aspect term and provide a first output corresponding to the aspect term; and a second self-attention network configured to, based on the output of the contextual language encoder, detect the aspect term and provide a second output corresponding to the aspect term; and based on the inputted batch of samples and a consistency loss function, selectively adjusting weights of the neural end-to-end ABSA system based on consistent aspect term detection by the first self-attention network and the second self-attention network.

Abstract: A speed estimation system includes: a detection module having a neural network configured to: receive a time series of images, the images including a surface having a local geometry; detect an object in the time series of images on the surface; determine pixel coordinates of the object in the time series of images, respectively; determine bounding boxes around the object in the time series of images, respectively; determine local mappings, which are not a function of global parameters describing the local geometry of the surface, between pixel coordinates and distance coordinates for the time series of images based on the bounding boxes around the object in the time series of images, respectively; and a speed module configured to determine a speed of the object traveling relative to the surface based on the distance coordinates determined for the time series of images.