An image analysis device comprising: an image acquisition unit, a feature amount calculation unit, a context calculation unit, a candidate region acquisition unit, a shape calculation unit, an extraction unit, a correction unit, and an output unit wherein: the image acquisition unit is configured to acquire a target image; the feature amount calculation unit is configured to calculate a feature map of the target image using a convolutional neural network; the context calculation unit is configured to calculate context score information representing context of each pixel in the target image on the basis of the feature map, wherein the context is semantic information representing meaning of an object, wherein the context score information includes a plurality of context scores, wherein each context score is information indicating which category the object belongs to; the candidate region acquisition unit is configured to extract region information specifying each of at least one candidate region included in the target image, wherein the candidate region is a region in which an object is probably present in the target image; the shape calculation unit is configured to calculate shape score information representing a shape of the object in each of the at least one candidate region included in the target image on the basis of the feature map and the region information wherein the shape score information includes a plurality of shape scores, wherein each shape score is mask information that indicates whether the object is present for each pixel, wherein each shape score is information that indicates one as the pixel representing the object and zero as the pixel representing a thing other than the object; the extraction unit is configured to extract the context score information in each of at least one candidate region on the basis of the context score information in the target image and the region information, cut out the context score information about a part corresponding to each candidate region from the context score information in the target image, and send, to the correction unit, the shape score information and the context score information in association with each other for each of at least one candidate region; the correction unit is configured to correct the shape score information in each of the at least one candidate region using the context score information in the corresponding candidate region by calculating corrected shape score information on the basis of values obtained by multiplying each shape score by each context score for each pixel; and the output unit is configured to output the context score information in the target image and the corrected shape score information in each of the at least one candidate region. the image acquisition unit is configured to acquire a target image; the feature amount calculation unit is configured to calculate a feature map of the target image using a convolutional neural network; the context calculation unit is configured to calculate context score information representing context of each pixel in the target image on the basis of the feature map, wherein the context is semantic information representing meaning of an object, wherein the context score information includes a plurality of context scores, wherein each context score is information indicating which category the object belongs to; the candidate region acquisition unit is configured to extract region information specifying each of at least one candidate region included in the target image, wherein the candidate region is a region in which an object is probably present in the target image; the shape calculation unit is configured to calculate shape score information representing a shape of the object in each of the at least one candidate region included in the target image on the basis of the feature map and the region information wherein the shape score information includes a plurality of shape scores, wherein each shape score is mask information that indicates whether the object is present for each pixel, wherein each shape score is information that indicates one as the pixel representing the object and zero as the pixel representing a thing other than the object; the extraction unit is configured to extract the context score information in each of at least one candidate region on the basis of the context score information in the target image and the region information, cut out the context score information about a part corresponding to each candidate region from the context score information in the target image, and send, to the correction unit, the shape score information and the context score information in association with each other for each of at least one candidate region; the correction unit is configured to correct the shape score information in each of the at least one candidate region using the context score information in the corresponding candidate region by calculating corrected shape score information on the basis of values obtained by multiplying each shape score by each context score for each pixel; and the output unit is configured to output the context score information in the target image and the corrected shape score information in each of the at least one candidate region.