Keypoint Estimation
Introduction Keypoint Estimation involves identifying and locating the significant points of an object image [1]. In the case of humans, each of these keypoints depicts the joints of different body parts like shoulder, elbow, knee, etc; a set of such keypoints can be associated to…
Fashion Attribute Tagging
Introduction Fashion automated tagging is the process of automatic generation of fashion attributes of products from an image. These fashion product taggings are very useful knowledge for cataloging purposes . With the advancement in Deep Learning , specifically in the field of Convolutional Neural Networks…
De-noising & Dust Detection
Introduction At Flixstock in addition to garment to on-model imagery, we need to ensure that the garment appears in its original form without any sort of imperfections, like dust, wrinkles etc. that might have gotten introduced during logistics. There is a common problem of dust…
Wrinkle, Lighting & Shadow Adjustment
Wrinkle removal is an important part of any image processing workflow which involves garment editing/retouching. Although current image editing softwares provides the tools for removing wrinkles from a garment image, it requires expert image editing skills to use these tools for wrinkle removal. Broadly, wrinkles…
Foreground Extraction
Introduction Foreground Extraction has been an active ongoing research in the computer vision community since the last two decades. The current state-of-the-art methods usually follow two different methodologies for foreground extraction; (a) Semantic segmentation, and (b) Alpha matting. The following sections discuss each of these…
Spatial Transformer Networks
Introduction Convolutional Neural Networks (CNNs) are a powerful class of models that perform incredibly well over a wide range of tasks such as classification, segmentation, object detection and more. For any model that distinguishes between images, it is highly desirable that in the learnt latent…