Book ChapterDOI
A New Technique for Accurate Segmentation, and Detection of Outfit Using Convolution Neural Networks
Priyal Jain,Abhishek Kankani,D. Geraldine Bessie Amali +2 more
- pp 169-177
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TLDR
This paper uses a large novel dataset and tools for labeling garment items, to retrieve similar style to help with clothing classification and shows that the general posture estimation issue can profit by apparel detection.Abstract:
Wearable Detection is a societally and economically critical yet a very challenging issue because of the number of layers and clothing someone could be wearing. Also layering, pose, body style, and shape become an issue. In this paper, we handle the wearable detection issue using recovery approaches. For model picture, we use the comparable styles from substantial database—labeled pictures and utilize cases to perceive dress things in the inquiry. Our tests come about moreover show that the general posture estimation issue can profit by apparel detection. In addition, for the correct detection and classification of what a person is wearing, we use the process of image segmentation and pose estimation to segment the image into superpixels and then analyze accordingly. In addition, we use a large novel dataset and tools for labeling garment items, to retrieve similar style to help with clothing classification.read more
Citations
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Journal ArticleDOI
Fashion sub-categories and attributes prediction model using deep learning
Book ChapterDOI
Accessible and Ethical Data Annotation with the Application of Gamification
TL;DR: This work proposes a method to use Gamification to streamline and simplify the data annotation process while eradicating its ethical concerns, which provides flexibility, scalability and reliability to the creation and improvement of labelled datasets while also improving ethicality and accessibility.
Journal ArticleDOI
Predicting clothing attributes with CNN and SURF based classification model
Navneet Kaur,Shreelekha Pandey +1 more
Posted Content
Smart Fashion: A Review of AI Applications in the Fashion & Apparel Industry.
TL;DR: In this paper, a comprehensive survey of fashion related research articles is presented, categorizing more than 580 related articles into 22 well-defined fashion-related tasks, and a time chart is provided to analyze the progress through the years.
References
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Proceedings ArticleDOI
Fully convolutional networks for semantic segmentation
TL;DR: The key insight is to build “fully convolutional” networks that take input of arbitrary size and produce correspondingly-sized output with efficient inference and learning.
Proceedings Article
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
TL;DR: This work presents iterative parameter estimation algorithms for conditional random fields and compares the performance of the resulting models to HMMs and MEMMs on synthetic and natural-language data.
Proceedings ArticleDOI
Real-time human pose recognition in parts from single depth images
Jamie Shotton,Andrew Fitzgibbon,Mat Cook,Toby Sharp,Mark J. Finocchio,Richard E. Moore,Alex Aben-Athar Kipman,Andrew Blake +7 more
TL;DR: This work takes an object recognition approach, designing an intermediate body parts representation that maps the difficult pose estimation problem into a simpler per-pixel classification problem, and generates confidence-scored 3D proposals of several body joints by reprojecting the classification result and finding local modes.
Proceedings ArticleDOI
Conditional Random Fields as Recurrent Neural Networks
Shuai Zheng,Sadeep Jayasumana,Bernardino Romera-Paredes,Vibhav Vineet,Zhizhong Su,Dalong Du,Chang Huang,Philip H. S. Torr +7 more
TL;DR: In this article, a new form of convolutional neural network that combines the strengths of Convolutional Neural Networks (CNNs) and Conditional Random Fields (CRFs)-based probabilistic graphical modelling is introduced.