Abstract: A computer-implemented method for vision transforming includes, for each of one or more channels of each of a set of tiles of an image: splitting the channel into at least a first channel portion and a second channel portion; processing the first channel portion using depthwise convolution; processing the second channel portion with multi-head self-attention; and combining the processed first channel portion and the processed second channel portion; and identifying an object in the image at least partially based on the combined processed first channel portion and processed second channel portion for each of the one or more channels of each of the set of tiles of the image.

Abstract: Embodiments of the present disclosure provide a method and an apparatus for determining a tag of a video, and a device, and relate to the field of artificial intelligence. In the method for determining a tag of a video in the present disclosure, a keyword library for labeling a video is first constructed based on text information of a plurality of videos. Video information of a to-be-labeled target video is determined, where the video information includes at least text information of the target video. Then, a video feature of the target video is determined based on the text information of the target video. Then, at least one keyword is determined from the keyword library as a tag of the target video based on the video feature. In this way, manual labeling is not needed, and labeling efficiency and accuracy are improved.

Abstract: An example apparatus for generating synthesized images includes a receiver to receive a frame, a mask and external images. The apparatus also includes a foreground augmenter to generate augmented foregrounds in the frame based on the mask. The apparatus includes a background augmenter to generate augmented backgrounds based on the frame, the mask, and the external images. The apparatus also further includes an image synthesizer to generate a synthesized image based on the generated augmented foregrounds and the augmented backgrounds.

Abstract: An example apparatus for generating synthesized images includes a receiver to receive a frame, a mask and external images. The apparatus also includes a foreground augmenter to generate augmented foregrounds in the frame based on the mask. The apparatus includes a background augmenter to generate augmented backgrounds based on the frame, the mask, and the external images. The apparatus also further includes an image synthesizer to generate a synthesized image based on the generated augmented foregrounds and the augmented backgrounds.