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A survey on Kornia: an Open Source Differentiable Computer Vision Library for PyTorch [article]

E. Riba, D. Mishkin, J. Shi, D. Ponsa, F. Moreno-Noguer, G. Bradski
2020 arXiv   pre-print
This work presents Kornia, an open source computer vision library built upon a set of differentiable routines and modules that aims to solve generic computer vision problems.  ...  The package uses PyTorch as its main backend, not only for efficiency but also to take advantage of the reverse auto-differentiation engine to define and compute the gradient of complex functions.  ...  The folks from the Open Source Vision Foundation and, and the PyTorch open-source community for helpful contributions and feedback.  ... 
arXiv:2009.10521v1 fatcat:wjyp5nzbfzfmjpvuxfaxydh5ra

Self-Distilled Hashing for Deep Image Retrieval [article]

Young Kyun Jang, Geonmo Gu, Byungsoo Ko, Nam Ik Cho
2021 arXiv   pre-print
Ultimately, we construct a deep hashing framework that generates discriminative hash codes.  ...  In this work, we propose a novel self-distilled hashing scheme to minimize the discrepancy while exploiting the potential of augmented data.  ...  window7 224, from timm 2 open source library respectively.  ... 
arXiv:2112.08816v1 fatcat:32wo44a3yfdmjp7hmsflvtchui

Consensus Clustering With Unsupervised Representation Learning [article]

Jayanth Reddy Regatti, Aniket Anand Deshmukh, Eren Manavoglu, Urun Dogan
2021 arXiv   pre-print
on some popular computer vision datasets.  ...  We propose a novel consensus clustering based loss function, and train BYOL with the proposed loss in an end-to-end way that improves the clustering ability and outperforms similar clustering based methods  ...  The color transformations were computed using Kornia [32] which is a differentiable computer vision library for Pytorch.  ... 
arXiv:2010.01245v2 fatcat:cwsojtbd2bbhxmpr7jpahymfwm