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Published:
This paper introduces an unsupervised method to generate masks(ðŸŽ) for facial datasets (😀) without any human annotations involved.
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SDEdit is an image synthesis and editing framework based on stochastic differential equations (SDEs). SDEdit allows stroke-based image synthesis, stroke-based image editing and image compositing without task specific optimization.
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An interesting method has come up that edits facial attributes, without allowing the loss of tattoos and pimples. This report will be a journey through this paper.
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This paper aims to make GAN inversion and interpretability possible. Through the lens of differential geometry, the authors propose that the metric tensor has various interpretability properties – by realising it as the Hessian matrix of the distance metric.
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This report presents and summarizes the latest developments in Score based generative models – with a goal to enable better understanding of existing approaches, new sampling algorithms, exact likelihood computation and conditional generation abilties to the family of score based generative models.
Short description of portfolio item number 1
Short description of portfolio item number 2
Published in accepted for NeurIPS 2020 Workshop TDA and Beyond as Spotlight presentation., 2020
A Topology Constrained Noise Sampling for GANs
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Published in accepted for IEEE Geoscience and Remote Sensing Letters (3.833 Impact Factor), 2020
Unsupervised Dual Attention Reconstruction Network for Hyperspectral Band Selection.
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slides are available here
slides are available here
slides are available here
slides are available here
slides are available here
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.