Abstract: Disclosed are systems, methods, and computer-readable storage media to perform an interactive image recolorization process. The method includes receiving user input including a stroke drawn on an image presented on a client device. The stroke comprises a user-specified color. The method further includes determining a region of interest in the image. The method further includes recolorizing the region of interest on the image based on the user-specified color and causing presentation of a result of the recolorization on the client device.

Abstract: Disclosed are systems, methods, and computer-readable storage media to perform an interactive image recolorization process. The method includes receiving user input including a stroke drawn on an image presented on a client device. The stroke comprises a user-specified color. The method further includes determining a region of interest in the image. The method further includes recolorizing the region of interest on the image based on the user-specified color and causing presentation of a result of the recolorization on the client device.

Abstract: Disclosed are techniques for providing relevant results for queries. A method can be implemented by a server computing device, and includes (1) receiving a query from a client computing device, (2) providing the query to a first machine learning (ML) model to produce a text answer to the query, (3) providing, to a second ML model, (i) the query, and (ii) the text answer, to obtain one or more digital assets that correspond to the query and the text answer, (4) generating results based on (i) the query, (ii) the text answer, and (iii) the one or more digital assets, and (5) causing the results to be output by way of a user interface on the client computing device. Other embodiments include generating text answers that include a plurality of text segments, where at least one image is obtained for each text segment of the plurality of text segments.

Abstract: The present disclosure generally relates to generating a video corresponding to a memory (e.g., an event or context) from media assets on a device. In some embodiments, the device receives user inputs requesting a video based on a natural language description of a memory. The device sends information of the natural language description to a first machine-learning (ML) model, and receives query tokens, which are used to find media items on the device that match the query tokens. The device sends information representing the found media items to another ML model that determines traits from the media items. These traits are sent to a third ML model to generate a story outline, and the video is generated by comparing the descriptions of shots in the story outline to visual embeddings of the found media assets to curate and arrange them into the video consistent with the story outline.

Abstract: Provided is a MART-1 (27-35) epitope-specific T cell receptor, comprising an ? chain and a ? chain. The ? chain comprises three complementary determining regions, respective sequences thereof being positions 61-66, positions 84-89, and positions 124-136 of SEQ ID No. 3. The ? chain comprises three complementary determining regions, respective amino acid sequences thereof being positions 46-50, positions 68-73, and positions 112-125 of SEQ ID No. 4. A T cell expressing the TCR can effectively recognize a MART-1 (27-35) epitope polypeptide supported on a T2 cell and secrete IFN-?, thereby demonstrating the functionality of the receptor. Use of the TCR with a relevant drug target allows for effective drug development.

Abstract: The technical problem of removing an object depicted in a selected region of an image to create a natural-looking edited image is addressed by providing systems, methods, and computer-readable storage media to perform automatic image inpainting. The method includes replacing the selected region using a color mask. A color mask can be generated using a mean color of pixels from a portion of the image that is distinct from and outside of the selected region.

Abstract: The technical problem of removing an object depicted in a selected region of an image to create a natural-looking edited image is addressed by providing systems, methods, and computer-readable storage media to perform automatic image inpainting. The method includes replacing the selected region using a color mask. A color mask can be generated using a mean color of pixels from a portion of the image that is distinct from and outside of the selected region.

Abstract: Disclosed are systems, methods, and computer-readable storage media to perform an interactive image recolorization process. The method includes receiving user input including a stroke drawn on an image presented on a client device. The stroke comprises a user-specified color. The method further includes determining a region of interest in the image. The method further includes recolorizing the region of interest on the image based on the user-specified color and causing presentation of a result of the recolorization on the client device.

Abstract: Disclosed are systems, methods, and computer-readable storage media to enhance an image on a mobile computing device. In some aspects, a user interface on the mobile computing device provides a plurality of image filters, each of the image filters associated with a different replacement sky type. Upon application of one of the plurality of image filters to an image, the mobile computing device is configured to identify a sky portion of the image, modify a color mapping of a non-sky portion of the image, and replace the sky portion of the image with replacement sky data corresponding to the applied image filter.

Abstract: An active depth detection system can generate a depth map from an image and user interaction data, such as a pair of clicks. The active depth detection system can be implemented as a recurrent neural network that can receive the user interaction data as runtime inputs after training. The active depth detection system can store the generated depth map for further processing, such as image manipulation or real-world object detection.

Abstract: Disclosed are systems, methods, and computer-readable storage media to perform an interactive image recolorization process. The method includes receiving user input including a stroke drawn on an image presented on a client device. The stroke comprises a user-specified color. The method further includes determining a region of interest in the image. The method further includes recolorizing the region of interest on the image based on the user-specified color and causing presentation of a result of the recolorization on the client device.

Abstract: The technical problem of removing an object depicted in a selected region of an image to create a natural-looking edited image is addressed by providing systems, methods, and computer-readable storage media to perform automatic image inpainting. The method includes replacing the selected region using a color mask. A color mask can be generated using a mean color of pixels from a portion of the image that is distinct from and outside of the selected region.

Abstract: Provided is a MART-1 (27-35) epitope-specific T cell receptor, comprising an ? chain and a ? chain. The ? chain comprises three complementary determining regions, respective sequences thereof being positions 61-66, positions 84-89, and positions 124-136 of SEQ ID No. 3. The ? chain comprises three complementary determining regions, respective amino acid sequences thereof being positions 46-50, positions 68-73, and positions 112-125 of SEQ ID No. 4. A T cell expressing the TCR can effectively recognize a MART-1 (27-35) epitope polypeptide supported on a T2 cell and secrete IFN-?, thereby demonstrating the functionality of the receptor. Use of the TCR with a relevant drug target allows for effective drug development.

Abstract: Various embodiments provide for systems, methods, and computer-readable storage media for annotating a digital image with a texture fill. An annotation system may receive a user input defining a border separating a first portion of a target digital image from a second portion of the target digital image. The annotation system may then generate a contour mask, such as a binary mask, for the target digital image based on the user-defined border. The annotation system may then apply a media overlay to the target image based on the contour mask. In particular, the contour mask can define portions of the target digital image such that the annotation system will apply a media overlay to at least one of those portions while not applying the media overlay to remaining portions of the target digital image.

Abstract: Disclosed are systems, methods, and computer-readable storage media to enhance an image on a mobile computing device. In some aspects, a user interface on the mobile computing device provides a plurality of image filters, each of the image filters associated with a different replacement sky type. Upon application of one of the plurality of image filters to an image, the mobile computing device is configured to identify a sky portion of the image, modify a color mapping of a non-sky portion of the image, and replace the sky portion of the image with replacement sky data corresponding to the applied image filter.

Abstract: An active depth detection system can generate a depth map from an image and user interaction data, such as a pair of clicks. The active depth detection system can be implemented as a recurrent neural network that can receive the user interaction data as runtime inputs after training. The active depth detection system can store the generated depth map for further processing, such as image manipulation or real-world object detection.

Abstract: Disclosed are systems, methods, and computer-readable storage media to enhance an image on a mobile computing device. In some aspects, a user interface on the mobile computing device provides a plurality of image filters, each of the image filters associated with a different replacement sky type. Upon application of one of the plurality of image filters to an image, the mobile computing device is configured to identify a sky portion of the image, modify a color mapping of a non-sky portion of the image, and replace the sky portion of the image with replacement sky data corresponding to the applied image filter.

Abstract: An active depth detection system can generate a depth map from an image and user interaction data, such as a pair of clicks. The active depth detection system can be implemented as a recurrent neural network that can receive the user interaction data as runtime inputs after training. The active depth detection system can store the generated depth map for further processing, such as image manipulation or real-world object detection.

Abstract: Disclosed are systems, methods, and computer-readable storage media to perform an interactive image recolorization process. The method includes receiving user input including a stroke drawn on an image presented on a client device. The stroke comprises a user-specified color. The method further includes determining a region of interest in the image. The method further includes recolorizing the region of interest on the image based on the user-specified color and causing presentation of a result of the recolorization on the client device.

Abstract: The technical problem of removing an object depicted in a selected region of an image to create a natural-looking edited image is addressed by providing systems, methods, and computer-readable storage media to perform automatic image inpainting. The method includes replacing the selected region using a color mask. A color mask can be generated using a mean color of pixels from a portion of the image that is distinct from and outside of the selected region.