Abstract: The present disclosure relates to an image processing method and device, an electronic apparatus and a storage medium. The method comprises: performing feature extraction on an image to be processed to obtain a first feature map of the image to be processed; splitting the first feature map into a plurality of first sub-feature maps according to dimension information of the first feature map and a preset splitting rule, wherein the dimension information of the first feature map comprises dimensions of the first feature map and size of each dimension; performing normalization on the plurality of first sub-feature maps respectively to obtain a plurality of second sub-feature maps; and splicing the plurality of second sub-feature maps to obtain a second feature map of the image to be processed. Embodiments of the present disclosure can reduce the statistical errors during normalization of a complete feature map.

Abstract: The present disclosure relates to a method and apparatus for recognizing a sequence in an image, an electronic device, and a storage medium. The method includes: performing feature extraction on a to-be-processed image to obtain a first feature map of the to-be-processed image, where the to-be-processed image includes a sequence formed by stacking at least one object along a stacking direction; determining a region feature of each segmented region in the to-be-processed image based on the first feature map, where all segmented regions are obtained by dividing the to-be-processed image into k regions along the stacking direction, k is a set number of objects stacked along the stacking direction, and k is an integer greater than 1; and determining a category of each object in the sequence based on the region feature of each segmented region. Embodiments of the present disclosure may implement recognition of stacked objects in a sequence.

Abstract: The present disclosure relates to a method and apparatus for recognizing stacked objects, an electronic device, and a storage medium. The method for recognizing stacked objects includes: obtaining a to-be-recognized image, wherein the to-be-recognized image includes a sequence formed by stacking at least one object along a stacking direction; performing feature extraction on the to-be-recognized image to obtain a feature map of the to-be-recognized image; and recognizing a category of the at least one object in the sequence according to the feature map. The embodiments of the present disclosure may implement accurate recognition of the category of stacked objects.

Abstract: The present disclosure relates to a method and apparatus for recognizing a sequence in an image, an electronic device, and a storage medium. The method includes: performing feature extraction on a to-be-processed image to obtain a first feature map of the to-be-processed image, where the to-be-processed image includes a sequence formed by stacking at least one object along a stacking direction; determining a region feature of each segmented region in the to-be-processed image based on the first feature map, where all segmented regions are obtained by dividing the to-be-processed image into k regions along the stacking direction, k is a set number of objects stacked along the stacking direction, and k is an integer greater than 1; and determining a category of each object in the sequence based on the region feature of each segmented region. Embodiments of the present disclosure may implement recognition of stacked objects in a sequence.

Abstract: The present disclosure relates to an image processing method and device, an electronic apparatus and a storage medium. The method comprises: performing feature extraction on an image to be processed to obtain a first feature map of the image to be processed; splitting the first feature map into a plurality of first sub-feature maps according to dimension information of the first feature map and a preset splitting rule, wherein the dimension information of the first feature map comprises dimensions of the first feature map and size of each dimension; performing normalization on the plurality of first sub-feature maps respectively to obtain a plurality of second sub-feature maps; and splicing the plurality of second sub-feature maps to obtain a second feature map of the image to be processed. Embodiments of the present disclosure can reduce the statistical errors during normalization of a complete feature map.

Abstract: The present disclosure relates to an image processing method and device, an electronic apparatus and a storage medium, the method comprising: performing, by a feature extraction network, feature extraction on an image to be processed to obtain a first feature map of the image to be processed; performing, by an M-level encoding network, scale-down and multi-scale fusion processing on the first feature map to obtain a plurality of feature maps which are encoded, each of the plurality of feature maps having a different scale; and performing, by an N-level decoding network, scale-up and multi-scale fusion processing on the plurality of feature maps which are encoded to obtain a prediction result of the image to be processed. Embodiments of the present disclosure are capable of improving the quality and robustness of the prediction result.