A computer-implemented method for automatically generating a video for an item listing in an e-commerce system, the method comprising: receiving a set of images, wherein the set of images comprises a plurality of images received as part of the item listing; generating a set of visual descriptors for the set of images, wherein generating the set of visual descriptors comprises computing a visual descriptor, using a first machine-learning model, for each image in the set of images; comparing visual descriptors from the set of visual descriptors to identify one or more redundant images in the set of images; generating, based on the compared visual descriptors, a unique set of images by removing the one or more redundant images from the set of images; determining, based on the unique set of images, an ordered set of images, wherein the ordered set of images is ordered based at least upon a category of the item listing; automatically determining, using additional data from the item listing, text associated with one or more images in the ordered set of images, wherein the text associated with the one or more images is automatically added to the one or more images; automatically generating, based on the ordered set of images, a video (220, 320), wherein the video (220, 320) comprises the ordered set of images; extracting a video frame from the video, wherein the video frame includes the image; generating a feature map for the video frame, wherein the feature map includes a plurality of feature points indicating locations of at least an edge of an item depicted in the image; determining, based on the feature map, a region in the video frame using a second machine-learning model; determining a textual attribute based on one or more attributes of the region using the second machine-learning model, wherein the textual attribute include at least color or size of the text, and wherein the one or more attributes of the region include one or more colors appearing in the region; inserting the text into the region using the textual attribute; and providing the video with inserted text as part of the item listing. receiving a set of images, wherein the set of images comprises a plurality of images received as part of the item listing; generating a set of visual descriptors for the set of images, wherein generating the set of visual descriptors comprises computing a visual descriptor, using a first machine-learning model, for each image in the set of images; comparing visual descriptors from the set of visual descriptors to identify one or more redundant images in the set of images; generating, based on the compared visual descriptors, a unique set of images by removing the one or more redundant images from the set of images; determining, based on the unique set of images, an ordered set of images, wherein the ordered set of images is ordered based at least upon a category of the item listing; automatically determining, using additional data from the item listing, text associated with one or more images in the ordered set of images, wherein the text associated with the one or more images is automatically added to the one or more images; automatically generating, based on the ordered set of images, a video (220, 320), wherein the video (220, 320) comprises the ordered set of images; extracting a video frame from the video, wherein the video frame includes the image; generating a feature map for the video frame, wherein the feature map includes a plurality of feature points indicating locations of at least an edge of an item depicted in the image; determining, based on the feature map, a region in the video frame using a second machine-learning model; determining a textual attribute based on one or more attributes of the region using the second machine-learning model, wherein the textual attribute include at least color or size of the text, and wherein the one or more attributes of the region include one or more colors appearing in the region; inserting the text into the region using the textual attribute; and providing the video with inserted text as part of the item listing.