Abstract: A method and apparatus for processing a video is provided. A current image frame of a video and a mask for a first area are obtained. The Image included in the first area is to be removed from the current image frame. A first resultant image of the current image frame is obtained with an image processing network based on the current image frame and the mask. The first resultant image is an image from which the image included in the first area is removed from the current image frame. A second resultant image of a previous image frame of the current image frame is obtained. The second resultant image is an image from which the image included in the second area is removed from the previous image frame. A final resultant image of the current image frame is obtained by fusing the first resultant image and the second resultant image.

Abstract: A method and apparatus for processing a video is provided. A current image frame of a video and a mask for a first area are obtained. The Image included in the first area is to be removed from the current image frame. A first resultant image of the current image frame is obtained with an image processing network based on the current image frame and the mask. The first resultant image is an image from which the image included in the first area is removed from the current image frame. A second resultant image of a previous image frame of the current image frame is obtained. The second resultant image is an image from which the image included in the second area is removed from the previous image frame. A final resultant image of the current image frame is obtained by fusing the first resultant image and the second resultant image.

Abstract: An image processing method performed by a computing device deployed with a deep-learning neural network is provided. An image, including an object to be segmented from the image, is acquired. The object is segmented from the image by using the deep-learning neural network to acquire a first segmentation result. Correction information input by a user with respect to the first segmentation result is acquired. Based on correction information, the first segmentation result is modified by using the deep-learning neural network, to acquire a second segmentation result.

Abstract: An image processing method performed by a computing device deployed with a deep-learning neural network is provided. An image, including an object to be segmented from the image, is acquired. The object is segmented from the image by using the deep-learning neural network to acquire a first segmentation result. Correction information input by a user with respect to the first segmentation result is acquired. Based on correction information, the first segmentation result is modified by using the deep-learning neural network, to acquire a second segmentation result.