RenderNet: A deep convolutional network for differentiable rendering from 3D shapes

Thu Nguyen Phuoc; Chuan Li; Stephen Balaban; Yongliang Yang

RenderNet: A deep convolutional network for differentiable rendering from 3D shapes

Thu Nguyen Phuoc, Chuan Li, Stephen Balaban, Yongliang Yang

Lambda Labs

Research output: Contribution to conference › Paper › peer-review

84 Citations (SciVal)

311 Downloads (Pure)

Abstract

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 665992

Original language	English
Publication status	Published - 3 Dec 2018
Event	NIPS 2018 - 32nd Conference on Neural Information Processing Systems - Duration: 3 Dec 2018 → 8 Dec 2018

Conference

Conference	NIPS 2018 - 32nd Conference on Neural Information Processing Systems
Period	3/12/18 → 8/12/18

Access to Document

renderNet_nips18.PDFAccepted author manuscript, 2.88 MB

https://papers.nips.cc/paper/2018/file/68d3743587f71fbaa5062152985aff40-Paper.pdf

Centre for the Analysis of Motion, Entertainment Research and Applications (CAMERA)
Cosker, D. (PI), Bilzon, J. (CoI), Campbell, N. (CoI), Cazzola, D. (CoI), Colyer, S. (CoI), Fincham Haines, T. (CoI), Hall, P. (CoI), Kim, K. I. (CoI), Lutteroth, C. (CoI), McGuigan, P. (CoI), O'Neill, E. (CoI), Richardt, C. (CoI), Salo, A. (CoI), Seminati, E. (CoI), Tabor, A. (CoI) & Yang, Y. (CoI)
Engineering and Physical Sciences Research Council
1/09/15 → 28/02/21
Project: Research council

Cite this

@conference{e64f66071e0148af98f18d42d1d1e89c,

title = "RenderNet: A deep convolutional network for differentiable rendering from 3D shapes",

abstract = "This project has received funding from the European Union{\textquoteright}s Horizon 2020 research and innovation programme under the Marie Sk{\l}odowska-Curie grant agreement No 665992 ",

author = "{Nguyen Phuoc}, Thu and Chuan Li and Stephen Balaban and Yongliang Yang",

year = "2018",

month = dec,

day = "3",

language = "English",

note = "NIPS 2018 - 32nd Conference on Neural Information Processing Systems ; Conference date: 03-12-2018 Through 08-12-2018",

}

TY - CONF

T1 - RenderNet: A deep convolutional network for differentiable rendering from 3D shapes

AU - Nguyen Phuoc, Thu

AU - Li, Chuan

AU - Balaban, Stephen

AU - Yang, Yongliang

PY - 2018/12/3

Y1 - 2018/12/3

N2 - This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 665992

AB - This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 665992

M3 - Paper

T2 - NIPS 2018 - 32nd Conference on Neural Information Processing Systems

Y2 - 3 December 2018 through 8 December 2018

ER -

RenderNet: A deep convolutional network for differentiable rendering from 3D shapes

Abstract

Conference

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Projects

Centre for the Analysis of Motion, Entertainment Research and Applications (CAMERA)

Cite this