Justus Thies: Our state of the art report on neural rendering is online.
#EGEV2020 #NeuralRendering https://t.co/0ccuikUL9c
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roadrunner01: State of the Art on Neural Rendering
abs: https://arxiv.org/abs/2004.03805 https://t.co/NxI7Fg6hcN
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Vincent Sitzmann: Neural Rendering offers new approaches to computer graphics, inverse graphics, and computer vision. In our state-of-the-art report, we compiled an overview over this emerging field - check it out!
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Mean Squared Error: State of the Art on Neural Rendering is a report published in Eurographics 2020, featuring an ensemble list of authors who have worked on novel research towards synthesizing graphics with neural networks since ~2015 https://arxiv.org/pdf/2004.03805.pdf https://t.co/HKqh5yrW0j
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Underfox: In this paper is provided a great survey on of neural rendering, with focus on approaches that combine classic computer graphics techniques with deep generative models to obtain controllable and photo-realistic outputs. #DeepLearning
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Sean Ryan Fanello: If you are interested in the state-of-art in #NeuralRendering check out our STAR report! This was a very fun collaboration with many great friends and researchers from all over the world! https://arxiv.org/pdf/2004.03805.pdf #DeepLearning #ComputerGraphics #Relighting #VolumetricCapture
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David Finsterwalder: Everyone in computer graphics not aware of #neuralrendering should have look at the recent paper "State of the Art on Neural Rendering" to get a great overview on the topic: https://arxiv.org/abs/2004.03805 2/4
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Daisuke Okanohara: An excellent survey on neural rendering. Not only the quality of generated images but also the controllability of the generation process are important. Covers many generative models, rendering with learned components, and image/video editing. https://arxiv.org/abs/2004.03805
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Jamie Shotton: Looking forward to reading this. Such an exciting area.
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Found on Apr 09 2020 at https://arxiv.org/pdf/2004.03805.pdf