Abstract: A method receives a video. The method analyzes information for a pixel of a frame in the video to determine a first value and a second value for the pixel. The first value is based on an image structure formed by the pixel in the frame and the second value is based on interframe motion of the image structure at the pixel. A third value is determined for an amount of judder based on the first value and the second value. The method outputs the third value to evaluate the video.

Abstract: A system includes a hardware processor and a memory storing a video/audio (V/A) synchronizer including video and audio encoders. The hardware processor executes the V/A synchronizer to receive raw video and audio extracted from media content, partition the raw video into video frame patches, partition the raw audio into audio samples, pre-process the video frame patches and the audio samples for encoding. The hardware processor further executes the V/A synchronizer to encode, using the video encoder, the pre-processed video frame patches to provide pre-processed and encoded video frame patches used to provide a latent representation of the raw video, encode, using the audio encoder, the pre-processed audio samples to provide pre-processed and encoded audio samples used to provide a latent representation of the raw audio, and synchronize, using the latent representations of the raw video and the raw audio, the raw audio with the raw video.

Abstract: A system includes a hardware processor, and a memory storing a software code and at least one machine learning (ML) model trained to distinguish between a plurality of content types. The hardware processor executes the software code to receive a content file including data identifying a dataset contained by the content file as being a first content type of the plurality of content types; predict, using the at least one ML model and the dataset, based on at least one image parameter, a first probability that a content type of the dataset matches the first content type identified by the data; and determine, based on the first probability, that the content type of the dataset (i) is the first content type identified by the data, (ii) is not the first 10 content type identified by the data, or (iii) is of an indeterminate content type.

Abstract: A system includes a hardware processor and a memory storing a video/audio (V/A) synchronizer including video and audio encoders. The hardware processor executes the V/A synchronizer to receive raw video and audio extracted from media content, partition the raw video into video frame patches, partition the raw audio into audio samples, pre-process the video frame patches and the audio samples for encoding. The hardware processor further executes the V/A synchronizer to encode, using the video encoder, the pre-processed video frame patches to provide pre-processed and encoded video frame patches used to provide a latent representation of the raw video, encode, using the audio encoder, the pre-processed audio samples to provide pre-processed and encoded audio samples used to provide a latent representation of the raw audio, and synchronize, using the latent representations of the raw video and the raw audio, the raw audio with the raw video.

Abstract: A system includes a hardware processor, and a memory storing a software code and at least one machine learning (ML) model trained to distinguish between a plurality of content types. The hardware processor executes the software code to receive a content file including data identifying a dataset contained by the content file as being a first content type of the plurality of content types; predict, using the at least one ML model and the dataset, based on at least one image parameter, a first probability that a content type of the dataset matches the first content type identified by the data; and determine, based on the first probability, that the content type of the dataset (i) is the first content type identified by the data, (ii) is not the first content type identified by the data, or (iii) is of an indeterminate content type.

Abstract: A system includes a hardware processor and a memory storing a video/audio (V/A) synchronizer including video and audio encoders. The hardware processor executes the V/A synchronizer to receive raw video and audio extracted from media content, partition the raw video into video frame patches, partition the raw audio into audio samples, pre-process the video frame patches and the audio samples for encoding. The hardware processor further executes the V/A synchronizer to encode, using the video encoder, the pre-processed video frame patches to provide pre-processed and encoded video frame patches used to provide a latent representation of the raw video, encode, using the audio encoder, the pre-processed audio samples to provide pre-processed and encoded audio samples used to provide a latent representation of the raw audio, and synchronize, using the latent representations of the raw video and the raw audio, the raw audio with the raw video.

Abstract: A method receives a video. The method analyzes information for a pixel of a frame in the video to determine a first value and a second value for the pixel. The first value is based on an image structure formed by the pixel in the frame and the second value is based on interframe motion of the image structure at the pixel. A third value is determined for an amount of judder based on the first value and the second value. The method outputs the third value to evaluate the video.

Abstract: A system includes a hardware processor, and a memory storing a software code and at least one machine learning (ML) model trained to distinguish between a plurality of content types. The hardware processor executes the software code to receive a content file including data identifying a dataset contained by the content file as being a first content type of the plurality of content types; predict, using the at least one ML model and the dataset, based on at least one image parameter, a first probability that a content type of the dataset matches the first content type identified by the data; and determine, based on the first probability, that the content type of the dataset (i) is the first content type identified by the data, (ii) is not the first content type identified by the data, or (iii) is of an indeterminate content type.