Publication
Publications
SieveNet: A Unified Framework for Robust Image-based Virtual Try-On
Ayush Chopra*, Surgan Jandial*, Kumar Ayush*, Mayur Hemani, Balaji K.
IEEE Winter on Applications of Computer Vision WACV 2020
Towards A Unified Framework for Visual Compatibility Prediction
Ayush Chopra*, Kumar Ayush*, Anirudh Singhal, Utkarsh Patel, Balaji K.
IEEE Winter on Applications of Computer Vision WACV 2020
Powering Robust Fashion Retrieval with Information Rich Feature Embeddings
Ayush Chopra, Abhishek Sinha, Mausoom Sarkar, Hiresh Gupta, Kumar Ayush, Balaji K.
International Conference on Computer Vision and Pattern Recognition 2019 Workshops CVPRW 2019 Best Paper Award.
Powering Virtual Try-On via Auxiliary Human Segmentation Learning
Kumar Ayush*, Surgan Jandial*, Ayush Chopra*, Balaji K.
International Conference on Computer Vision 2019 Workshops ICCVW 2019
Robust Cloth Warping via Multi-Scale Patch Adversarial Loss for Virtual Try-On Framework
Kumar Ayush*, Surgan Jandial*, Ayush Chopra*, Balaji K.
International Conference on Computer Vision 2019 Workshops ICCVW 2019
Pose Aware Fine Grained Visual Classification for Fashion
Kushagra Mahajan*, Tarasha Khurana*, Ayush Chopra*, Chetan Arora, Isha Gupta.
25th IEEE International Conference on Image Processing. ICIP 2018
Hierarchy Influenced Differential Evolution: A Motor Operation Inspired Approach
Shubham Dokania, Ayush Chopra, Feroz Ahmad, Anil Singh Parihar.
9th International Joint Conference on Computational Intelligence. IJCCI 2017
Biocidal and Antistatic Performance of fabric modified with Polyaniline Microtubes
Ayush Chopra, Hema Bhandari, S.K Dhawan.
Conference on Environmental Economics and Social Sustainability
Patents
Retrospection: An Online Mining Technique for Efficient Training of Deep Neural Networks. (In filing)
Accurately Generating Virtual Try-on Images Utilizing A Unified Neural Network Framework. (US 16/679,165)
Cloth Warping Using Multi-Scale Patch Adversarial Loss. (US 16/673,574)
Entropy Based Synthetic Data Generation For Augmenting Classification System Training Data. (US 16/659,147)
Generating Combined Feature Embeddings For Minority Class Upsampling In Training Machine Learning Models With Imbalanced Samples. (US 16/564,531)
Improving Performance of Neural Networks Using Learned Specialized Transformation Functions. (US 16/534,856)
Identifying Digital Attributes from Multiple Attribute Groups Within Target Digital Images Utilizing Deep Cognitive Attribution. (US 16/564,831)
Methods for Exploring and Recommending Matching Products Across Categories. (US 16/417,373)