Samsung Electronics Co., Ltd.

Afsaneh Fazly

Iqbal Ismail Mohomed

Allan Jepson

Konstantinos Derpanis

Ran Zhang

Caleb Ryan Phillips

Haotian Zhang

Mete Kemertas

Leila Pishdad

Federico Fancellu

Alborz Rezazadeh Sereshkeh

Gary Leung

Krish Perumal

Minfan Zhang

A method of personalized image retrieval includes obtaining a natural language query including a name; replacing the name in the natural language query with a generic term to provide an anonymized query and named entity information; obtaining a plurality of initial ranking scores and a plurality of attention weights corresponding to a plurality of images using a trained scoring model that inputs the anonymized query and the plurality of images; obtaining a plurality of delta scores corresponding to the plurality of images using a re-scoring model that inputs the plurality of attention weights and the named entity information; and obtaining a plurality of final ranking scores by modifying the plurality of initial ranking scores based on the plurality of delta scores. The trained scoring model performs semantic based searching and the re-scoring model determines a probability that faces detected in the plurality of images correspond to the name.

Method of personalized image and video searching based on a natural language query, and an apparatus for the same

An apparatus for providing similar contents, using a neural network, includes a memory storing instructions, and a processor configured to execute the instructions to obtain a plurality of similarity values between a user query and a plurality of images, using a similarity neural network, obtain a rank of each the obtained plurality of similarity values, and provide, as a most similar image to the user query, at least one among the plurality of images that has a respective one among the plurality of similarity values that corresponds to a highest rank among the obtained rank of each of the plurality of similarity values. The similarity neural network is trained with a divergence neural network for outputting a divergence between a first distribution of first similarity values for positive pairs, among the plurality of similarity values, and a second distribution of second similarity values for negative pairs, among the plurality of similarity values.

Apparatus for deep representation learning and method thereof

An utterance in any of various languages is processed to derive a predicted label using a generated grammar. The grammar is suitable for deriving meaning of utterances from several languages (polyglot). The utterance is processed by an encoder using word embeddings. The encoder and a decoder process the utterance using the polyglot grammar to obtain a machine-readable result. The machine-readable result is well-formed based on accounting for re-entrances of intermediate variable references. A machine then takes action on the machine-readable result. Ambiguity is reduced by the decoder by the well-formed machine-readable result. Sparseness of the generated polyglot grammar is reduced by using a two-pass approach including placeholders which are ultimately replaced by edge labels.

Machine action based on language-independent graph rewriting of an utterance

An apparatus for video searching, includes a memory storing instructions, and a processor configured to execute the instructions to split a video into scenes, obtain, from the scenes into which the video is split, one or more textual descriptors describing each of the scenes, encode the obtained one or more textual descriptors describing each of the scenes into a video scene vector of each of the scenes, encode a user query into a query vector having a same semantic representation as that of the video scene vector of each of the scenes into which the one or more textual descriptors describing each of the scenes are encoded, and identify whether the video scene vector of at least one among the scenes corresponds to the query vector into which the user query is encoded.

Apparatus for video searching using multi-modal criteria and method thereof

An apparatus for vision and language-assisted smartphone task automation, includes a processor configured to execute instructions to identify whether an utterance of a user refers to one among at least one existing automation script, and based on the utterance being identified to not refer to the one among the at least one existing automation script, capture one or more screenshots and one or more coordinates of a display, the one or more screenshots and the one or more coordinates corresponding to one or more interactions of the user with the display while the user is demonstrating a new automation script, perform object detection and optical character recognition on the captured one or more screenshots and the captured one or more coordinates to obtain user interface (UI) elements corresponding to the one or more interactions, and obtain the new automation script, based on the obtained UI elements.

Apparatus for vision and language-assisted smartphone task automation and method thereof

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Toronto, Canada

Afsaneh Fazly