Abstract:
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.
Abstract:
A social networking system selects and presents content items to a user via a feed. Additionally, the social networking system predicts heights associated with various content items, such as content items selected for presentation via the feed. Characteristics of a content item (e.g., a type of content included in the content item, a language of the content item, and a number of comments associated with the content item) as well as characteristics of a client device associated with the user are used to predict a height associated with the content item. When selecting content items for presentation to the user, the social networking system accounts for the predicted heights of various content items to increase the likelihood of the user interacting with content items presented via the feed.
Abstract:
A social networking system selects and presents content items to a user via a feed. Additionally, the social networking system predicts heights associated with various content items, such as content items selected for presentation via the feed. Characteristics of a content item (e.g., a type of content included in the content item, a language of the content item, and a number of comments associated with the content item) as well as characteristics of a client device associated with the user are used to predict a height associated with the content item. When selecting content items for presentation to the user, the social networking system accounts for the predicted heights of various content items to increase the likelihood of the user interacting with content items presented via the feed.
Abstract:
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.
Abstract:
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.
Abstract:
A social networking system selects and presents content items to a user via a feed. Additionally, the social networking system predicts heights associated with various content items, such as content items selected for presentation via the feed. Characteristics of a content item (e.g., a type of content included in the content item, a language of the content item, and a number of comments associated with the content item) as well as characteristics of a client device associated with the user are used to predict a height associated with the content item. When selecting content items for presentation to the user, the social networking system accounts for the predicted heights of various content items when ordering the content items in the news feed.