Facebook, Inc.

Renbin Peng

Evgeny V Kuzyakov

Lei Huang

Ziheng Wang

Jianyu Wang

Guangshuo Liu

Di Liu

Chien-Nan Chen

Chetan Parag Gupta

David Young Joon Pio

Raghu Prasad Chalasani

Systems, methods, and non-transitory computer-readable media can provide at least one frame of a content item to a saliency prediction model, the saliency prediction model being trained to identify salient points of interest that appear in content items. Information describing at least a first salient point of interest that appears in the at least one frame can be obtained from the saliency prediction model. The first salient point of interest can be predicted to be of interest to users accessing the content item. A view-based projection can be applied to a region corresponding to the first salient point of interest, wherein the view-based projection enhances a quality in which the region is presented.

Systems and methods for provisioning content

Systems, methods, and non-transitory computer-readable media can receive a set of video frames associated with a video. For each video frame of the set of video frames, a plurality of interest points are identified based on an interest point detector. For each video frame of the set of video frames, it is determined whether the video frame depicts the same static image as a next video frame in the set of video frames based on the plurality of interest points identified in each video frame.

Systems and methods for automated video classification

Systems, methods, and non-transitory computer-readable media can receive a set of video frames associated with a video. Dynamic regions in each video frame of the set of video frames can be filtered out, wherein each dynamic region represents a region in which a threshold level of movement is detected. A determination can be made for each video frame of the set of filtered video frames, whether the video frame comprises synthetic overlaid text based on a machine learning model.

Systems, methods, and non-transitory computer-readable media can receive a set of video frames associated with a video. A determination can be made that a first set of consecutive video frames of the set of video frames depicts identical content to a second set of consecutive video frames of the set of video frames, wherein the first set of consecutive video frames and the second set of consecutive video frames satisfy a threshold number of consecutive video frames. The video is identified as a looping video based on the determination that the first set of consecutive video frames depicts identical content to the second set of consecutive video frames.

Systems, methods, and non-transitory computer-readable media can receive a set of video frames associated with a video. A determination can be made that a threshold number of video frames of the set of video frames depict two or more reaction icons of a set of reaction icons. The video can be identified as a poll video based on the determining that the threshold number of video frames of the set of video frames depict two or more reaction icons of the set of reaction icons.

Systems, methods, and non-transitory computer-readable media can determine that a content item is being presented through a display screen of the computing device. Information describing one or more salient points of interest that appear during presentation of the content item are determined, wherein the salient points of interest are predicted to be of interest to one or more users accessing the content item. The presentation of at least a first salient point of interest is enhanced during presentation of the content item based at least in part on the information.

Systems and methods for presenting content

Systems, methods, and non-transitory computer-readable media can determine at least one salient point of interest in a frame of a content item based at least in part on a saliency prediction model, the saliency prediction model being trained to identify salient points of interest that appear in content items; determine a barrel projection representation for the frame; and apply a view-based projection to the barrel projection representation for the frame, wherein the view-based projection enhances a quality in which a region corresponding to the at least one salient point of interest is presented.

Systems and methods for provisioning content using barrel projection representation

Systems, methods, and non-transitory computer-readable media can generate a saliency prediction model for identifying salient points of interest that appear during presentation of content items, provide at least one frame of a content item to the saliency prediction model, and obtain information describing at least a first salient point of interest that appears in the at least one frame from the saliency prediction model, wherein the first salient point of interest is predicted to be of interest to one or more users accessing the content item.

Systems and methods for evaluating content

Systems, methods, and non-transitory computer-readable media can determine saliency information describing one or more salient points of interest that appear during presentation of a content item, wherein the salient points of interest are predicted to be of interest to one or more users accessing the content item and embed the saliency information describing the salient points of interest into the content item, wherein the saliency information is capable of being processed during presentation of the content item to enhance the presentation of the content item.

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Fremont, CA, United States of America

Renbin Peng