Abstract: The present disclosure relates to a video processing method and apparatus, a readable medium, and an electronic device. The method includes: acquiring a first highlight segment obtained by performing highlight recognition on a target video; displaying an editing page corresponding to the first target highlight segment in response to an editing instruction for a first target highlight segment, where the editing page is used by a user to perform an editing operation on the first target highlight segment; processing, according to the editing operation of the user, the first target highlight segment to obtain a second highlight segment; and posting the second highlight segment in response to receiving a posting instruction for the second highlight segment.

Abstract: Some examples of a sketch-based image recognition system may generate a model for identifying a subject of a sketch. The model is formed from a plurality of images having visual features similar to the visual features of the sketch. The model may include object topics representative of categories which may correspond to the subject of the sketch and shape topics representative of the visual features of the sketch.

Abstract: There is provided a signal processing apparatus including a learning unit that learns a plurality of base signals of which coefficients become sparse, for each of features of signals, such that the signals are represented by a linear operation of the plurality of base signals.

Abstract: Some examples of a sketch-based image recognition system may generate a model for identifying a subject of a sketch. The model is formed from a plurality of images having visual features similar to the visual features of the sketch. The model may include object topics representative of categories which may correspond to the subject of the sketch and shape topics representative of the visual features of the sketch.

Abstract: Some examples of a sketch-based image segmentation system may segment a hand-drawn sketch based on proximity, intuitive clues and semantic information. For instance, the system may cluster line segments of the sketch if the line segments are within a threshold distance. Further, the system may cluster line segments of the sketch based on a set of intuitive clues. In some implementations, a sketch-based search engine may be utilized to search an image collection to identify images with shape features similar to the sketch and to segment the sketch based on the semantic information associated with the identified images.

Abstract: Some examples of a sketch-based image recognition system may generate a model for identifying a subject of a sketch. The model is formed from a plurality of images having visual features similar to the visual features of the sketch. The model may include object topics representative of categories which may correspond to the subject of the sketch and shape topics representative of the visual features of the sketch.

Abstract: Some examples of a sketch-based image segmentation system may segment a hand-drawn sketch based on proximity, intuitive clues and semantic information. For instance, the system may cluster line segments of the sketch if the line segments are within a threshold distance. Further, the system may cluster line segments of the sketch based on a set of intuitive clues. In some implementations, a sketch-based search engine may be utilized to search an image collection to identify images with shape features similar to the sketch and to segment the sketch based on the semantic information associated with the identified images.

Abstract: Some examples of a sketch-based image recognition system may generate a model for identifying a subject of a sketch. The model is formed from a plurality of images having visual features similar to the visual features of the sketch. The model may include object topics representative of categories which may correspond to the subject of the sketch and shape topics representative of the visual features of the sketch.

Abstract: There is provided a signal processing apparatus including a learning unit that learns a plurality of base signals of which coefficients become sparse, using a cost function including a term showing a correspondence between the coefficients, such that signals are represented by a linear operation of the plurality of base signals.

Abstract: There is provided a signal processing apparatus including a learning unit that learns a plurality of base signals of which coefficients become sparse, for each of features of signals, such that the signals are represented by a linear operation of the plurality of base signals.