1. A computer-implemented method for selecting representative frames for videos, comprising: receiving a video including a set of frames; identifying a set of features for each of the frames of the video, wherein the set of features includes frame-based features and semantic features, and wherein each of the semantic features for a frame is identified by (i) transmitting a designation of the frame associated with the frame-based features to a plurality of semantic classifiers, (ii) receiving, from each of the plurality of semantic classifiers, a likelihood of a semantic concept being depicted in the frame of the video, and (iii) assigning a label corresponding to the semantic concept to the frame of the video based on the likelihood of the semantic concept being depicted in the frame of the video; generating a set of video segments for the video, each video segment including a chronological subset of frames from the video, and each frame associated with at least one of the semantic features; generating, for each video segment in the set of video segments, a score for each frame of the subset of frames of the video segment based at least on the semantic features; selecting a plurality of representative frames of the video, wherein each representative frame for each video segment in the set of video segments is selected based on the scores for the frames in the video segment, the representative frame representing and summarizing the video segment; and generating a summarized video that combines at least a portion of the plurality of representative frames of the video.