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Implicit Neural Representations (INRs) encoding continuous multi-media data via multi-layer perceptrons has shown undebatable promise in various computer vision tasks.
Object enhancement and extraction
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Fitting smooth surfaces to dense polygon meshes
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Region-based shape descriptor invariant to rotation, scale and translation
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Applications of Lie groups to differential equations
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Image processing done right
Jan J Koenderink and Andrea J van Doorn · 2002
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Geometric curve evolution and image processing
Frédéric Cao · 2003
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Linear light source reflectometry
Andrew Gardner, Chris Tchou, Tim Hawkins, and Paul Debevec · 2003
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On the kronecker product
Kathrin Schacke · 2004
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Geometric partial differential equations and image analysis
Guillermo Sapiro · 2006
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Image inpainting using a tv-stokes equation
Xue-Cheng Tai, Stanley Osher, and Randi Holm · 2007
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Total variation based image registration
Lars Hömke, Claudia Frohn-Schauf, Stefan Henn, and Kristian Witsch · 2007
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Clg method for optical flow estimation based on gradient constancy assumption
Adam Rabcewicz · 2007
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Advanced digital signal processing and noise reduction
Saeed V Vaseghi · 2008
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Designing partial differential equations for image processing by combining differental invariants, 2009
Zhouchen Lin, Wei Zhang, and Xiaoou Tang · 2009
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Learning pdes for image restoration via optimal control
Risheng Liu, Zhouchen Lin, Wei Zhang, and Zhixun Su · 2010
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Learning fast approximations of sparse coding
Karol Gregor and Yann LeCun · 2010
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On single image scale-up using sparse-representations
Roman Zeyde, Michael Elad, and Matan Protter · 2010
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Low-complexity single-image super-resolution based on nonnegative neighbor embedding
Marco Bevilacqua, Aline Roumy, Christine Guillemot, and Marie line Alberi Morel · 2012
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Symmetry in 3d geometry: Extraction and applications
Niloy J Mitra, Mark Pauly, Michael Wand, and Duygu Ceylan · 2013
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Geometry-driven diffusion in computer vision
Bart M Haar Romeny · 2013
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Adaptive partial differential equation learning for visual saliency detection
Risheng Liu, Junjie Cao, Zhouchen Lin, and Shiguang Shan · 2014
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An isotropic 3 × \times 3 image gradient operator, presentation at stanford ai project (1968), 2014
I Sobel · 2014
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Rolling guidance normal filter for geometric processing
Peng-Shuai Wang, Xiao-Ming Fu, Yang Liu, Xin Tong, Shi-Lin Liu, and Baining Guo · 2015
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Image style transfer using convolutional neural networks
Leon A Gatys, Alexander S Ecker, and Matthias Bethge · 2016
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Image restoration: Wavelet frame shrinkage, nonlinear evolution pdes, and beyond
Bin Dong, Qingtang Jiang, and Zuowei Shen · 2017
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Error bounds for approximations with deep relu networks
Dmitry Yarotsky · 2017
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Transferring image-based edits for multi-channel compositing
James W. Hennessey, Wilmot Li, Bryan Russell, Eli Shechtman, and Niloy J. Mitra · 2017
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Interactive 3d modeling with a generative adversarial network
Jerry Liu, Fisher Yu, and Thomas Funkhouser · 2017
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Ntire 2017 challenge on single image super-resolution: Dataset and study
Eirikur Agustsson and Radu Timofte · 2017
Implicit neural representations with periodic activation functions
Vincent Sitzmann, Julien Martel, Alexander Bergman, David Lindell, and Gordon Wetzstein · 2020
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Moiré pattern removal via attentive fractal network
Dejia Xu, Yihao Chu, and Qingyan Sun · 2020
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Coin: Compression with implicit neural representations
Emilien Dupont, Adam Goliński, Milad Alizadeh, Yee Whye Teh, and Arnaud Doucet · 2021
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Nerv: Neural representations for videos
Hao Chen, Bo He, Hanyu Wang, Yixuan Ren, Ser Nam Lim, and Abhinav Shrivastava · 2021
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Implicit neural video compression
Yunfan Zhang, Ties van Rozendaal, Johann Brehmer, Markus Nagel, and Taco Cohen · 2021
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2017
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Xception: Deep learning with depthwise separable convolutions
François Chollet · 2017
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Solving high-dimensional partial differential equations using deep learning
Jiequn Han, Arnulf Jentzen, and E Weinan · 2018
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Pde-net: Learning pdes from data
Zichao Long, Yiping Lu, Xianzhong Ma, and Bin Dong · 2018
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Neural ordinary differential equations
Ricky TQ Chen, Yulia Rubanova, Jesse Bettencourt, and David K Duvenaud · 2018
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Learning shape templates with structured implicit functions
Kyle Genova, Forrester Cole, Daniel Vlasic, Aaron Sarna, William T Freeman, and Thomas Funkhouser · 2019
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Vincent Sitzmann, Semon Rezchikov, William T Freeman, Joshua B Tenenbaum, and Fredo Durand · 2021
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Nerf in the dark: High dynamic range view synthesis from noisy raw images
Ben Mildenhall, Peter Hedman, Ricardo Martin-Brualla, Pratul Srinivasan, and Jonathan T Barron · 2021
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pi-gan: Periodic implicit generative adversarial networks for 3d-aware image synthesis
Eric R Chan, Marco Monteiro, Petr Kellnhofer, Jiajun Wu, and Gordon Wetzstein · 2021
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Unconstrained scene generation with locally conditioned radiance fields
Terrance DeVries, Miguel Angel Bautista, Nitish Srivastava, Graham W Taylor, and Joshua M Susskind · 2021
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Stylenerf: A style-based 3d-aware generator for high-resolution image synthesis
Jiatao Gu, Lingjie Liu, Peng Wang, and Christian Theobalt · 2021
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Gancraft: Unsupervised 3d neural rendering of minecraft worlds
Zekun Hao, Arun Mallya, Serge Belongie, and Ming-Yu Liu · 2021
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Gnerf: Gan-based neural radiance field without posed camera
Quan Meng, Anpei Chen, Haimin Luo, Minye Wu, Hao Su, Lan Xu, Xuming He, and Jingyi Yu · 2021
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Giraffe: Representing scenes as compositional generative neural feature fields
Michael Niemeyer and Andreas Geiger · 2021
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Cips-3d: A 3d-aware generator of gans based on conditionally-independent pixel synthesis
Peng Zhou, Lingxi Xie, Bingbing Ni, and Qi Tian · 2021
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Editing conditional radiance fields
Steven Liu, Xiuming Zhang, Zhoutong Zhang, Richard Zhang, Jun-Yan Zhu, and Bryan Russell · 2021
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Clip-nerf: Text-and-image driven manipulation of neural radiance fields
Can Wang, Menglei Chai, Mingming He, Dongdong Chen, and Jing Liao · 2021
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Cryodrgn: reconstruction of heterogeneous cryo-em structures using neural networks
Ellen D Zhong, Tristan Bepler, Bonnie Berger, and Joseph H Davis · 2021
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Autoint: Automatic integration for fast neural volume rendering
David B Lindell, Julien NP Martel, and Gordon Wetzstein · 2021
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In-place scene labelling and understanding with implicit scene representation
Shuaifeng Zhi, Tristan Laidlow, Stefan Leutenegger, and Andrew J Davison · 2021
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Nesf: Neural semantic fields for generalizable semantic segmentation of 3d scenes
Suhani Vora, Noha Radwan, Klaus Greff, Henning Meyer, Kyle Genova, Mehdi SM Sajjadi, Etienne Pot, Andrea Tagliasacchi, and Daniel Duckworth · 2021
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Signet: Efficient neural representation for light fields
Brandon Yushan Feng and Amitabh Varshney · 2021
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Learned initializations for optimizing coordinate-based neural representations
Matthew Tancik, Ben Mildenhall, Terrance Wang, Divi Schmidt, Pratul P Srinivasan, Jonathan T Barron, and Ren Ng · 2021
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Meta-learning sparse implicit neural representations
Jaeho Lee, Jihoon Tack, Namhoon Lee, and Jinwoo Shin · 2021
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Geometry processing with neural fields
Guandao Yang, Serge Belongie, Bharath Hariharan, and Vladlen Koltun · 2021
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Multi-stage progressive image restoration
Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Ming-Hsuan Yang, and Ling Shao · 2021
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Resolution-robust large mask inpainting with fourier convolutions
Roman Suvorov, Elizaveta Logacheva, Anton Mashikhin, Anastasia Remizova, Arsenii Ashukha, Aleksei Silvestrov, Naejin Kong, Harshith Goka, Kiwoong Park, and Victor Lempitsky · 2021
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From data to functa: Your data point is a function and you should treat it like one
Emilien Dupont, Hyunjik Kim, SM Eslami, Danilo Rezende, and Dan Rosenbaum · 2022
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Neural implicit dictionary learning via mixture-of-expert training
Peihao Wang, Zhiwen Fan, Tianlong Chen, and Zhangyang Wang · 2022
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Unified implicit neural stylization
Zhiwen Fan, Yifan Jiang, Peihao Wang, Xinyu Gong, Dejia Xu, and Zhangyang Wang · 2022
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Maxim: Multi-axis mlp for image processing
Zhengzhong Tu, Hossein Talebi, Han Zhang, Feng Yang, Peyman Milanfar, Alan Bovik, and Yinxiao Li · 2022
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