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Found 6 papers, 3 papers with code
MovingFashion: a Benchmark for the Video-to-Shop Challenge
Retrieving clothes which are worn in social media videos (Instagram, TikTok) is the latest frontier of e-fashion, referred to as "video-to-shop" in the computer vision literature.
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Texture Retrieval in the Wild through detection-based attributes
Capturing the essence of a textile image in a robust way is important to retrieve it in a large repository, especially if it has been acquired in the wild (by taking a photo of the textile of interest).
Texel-Att: Representing and Classifying Element-based Textures by Attributes
It first individuates texels, characterizing them with individual attributes; subsequently, texels are grouped and characterized through layout attributes, which give the Texel-Att representation.
SIMCO: SIMilarity-based object COunting
We present SIMCO, the first agnostic multi-class object counting approach.
Understanding Deep Architectures by Visual Summaries
In deep learning, visualization techniques extract the salient patterns exploited by deep networks for image classification, focusing on single images; no effort has been spent in investigating whether these patterns are systematically related to precise semantic entities over multiple images belonging to a same class, thus failing to capture the very understanding of the image class the network has realized.
Indirect Match Highlights Detection with Deep Convolutional Neural Networks
Highlights in a sport video are usually referred as actions that stimulate excitement or attract attention of the audience.
