CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images | Paper Citation Record

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This paper cites DOI:10.23919/TST.2017.8195348.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images DOI:10.23919/TST.2017.8195348

Reference 1

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This paper cites GRAF: Generative Radiance Fields for 3D-Aware Image Synthesis.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images GRAF: Generative Radiance Fields for 3D-Aware Image Synthesis

Reference 2

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This paper cites NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis

Reference 3

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Reference 4

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This paper cites Recent Progress on Generative Adver- sarial Networks (GANs): A Survey, IEEE Access, 36322-36333,2019.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images Recent Progress on Generative Adver- sarial Networks (GANs): A Survey, IEEE Access, 36322-36333,2019

Reference 5

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This paper cites UnsupervisedRepresentationLearningwithDeepConvolutionalNeu- ral Network for Remote Sensing Images, International Conference on Image & Graphics, 2017.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images UnsupervisedRepresentationLearningwithDeepConvolutionalNeu- ral Network for Remote Sensing Images, International Conference on Image & Graphics, 2017

Reference 6

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Observation 9eed5eeb-66b1-4db5-93a3-a8d1e2f8fb7c · outbound

This paper cites Conditional Generative Adversarial Nets.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images Conditional Generative Adversarial Nets

Reference 7

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Observation 34e8ad87-cfb0-4bcb-8892-9f88dd89ec8a · outbound

This paper cites Condi- tionalImageSynthesisWithAuxiliaryClassifierGANs,arXive-prints,.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images Condi- tionalImageSynthesisWithAuxiliaryClassifierGANs,arXive-prints,

Reference 8

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This paper cites InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets

Reference 9

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This paper cites Wasserstein generativeadversarialnetworks,InternationalConferenceonMachine Learning, 2017.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images Wasserstein generativeadversarialnetworks,InternationalConferenceonMachine Learning, 2017

Reference 10

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This paper cites Improved Training of Wasserstein GANs.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images Improved Training of Wasserstein GANs

Reference 11

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Observation 4955a38a-2bac-4692-8bc4-75aef29ed6a9 · outbound

This paper cites On the regularization of Wasserstein GANs.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images On the regularization of Wasserstein GANs

Reference 12

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This paper cites Progressive Growing of GANs for Improved Quality, Stability, and Variation.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images Progressive Growing of GANs for Improved Quality, Stability, and Variation

Reference 13

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This paper cites IEEE ICCV, 2017.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images IEEE ICCV, 2017

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Observation 7d9f99e1-d037-423a-bf6a-3ab81db609f3 · outbound

This paper cites IEEE Transactions on Pattern Analysis and Ma- chine Intelligence,PP,99, 2017.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images IEEE Transactions on Pattern Analysis and Ma- chine Intelligence,PP,99, 2017

Reference 15

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This paper cites High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs

Reference 16

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This paper cites A Style-Based Gen- erator Architecture for Generative Adversarial Networks, Conference on Computer Vision and Pattern Recognition (CVPR), IEEE, 2019.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images A Style-Based Gen- erator Architecture for Generative Adversarial Networks, Conference on Computer Vision and Pattern Recognition (CVPR), IEEE, 2019

Reference 17

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This paper cites High-Fidelity Synthesis with Disentangled Representation,.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images High-Fidelity Synthesis with Disentangled Representation,

Reference 18

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Observation 4fae0a54-245e-44ee-a3de-1e48a8f5a271 · outbound

This paper cites Semi-Supervised StyleGAN for Disentanglement Learning.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images Semi-Supervised StyleGAN for Disentanglement Learning

Reference 19

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This paper cites and Sohn, K.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images and Sohn, K

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This paper cites Advances in Neural Rendering, arXiv e-prints,.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images Advances in Neural Rendering, arXiv e-prints,

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This paper cites M and Weston, Nick.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images M and Weston, Nick

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CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images Unresolved cited work

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Observation 5bead8da-624c-4fbc-9876-7c38a1f7bc60 · outbound

This paper cites OctNet: Learning Deep 3D Representations at High Resolutions, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images OctNet: Learning Deep 3D Representations at High Resolutions, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),

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Observation f6b9688a-2eb2-4abd-b219-b94788b11f0c · outbound

This paper cites Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling

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This paper cites AtlasNet: A Papier-M\^ach\'e Approach to Learning 3D Surface Generation.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images AtlasNet: A Papier-M\^ach\'e Approach to Learning 3D Surface Generation

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This paper cites Deep March- ing Cubes: Learning Explicit Surface Representations, IEEE/CVF Conference on Computer Vision and Pattern Recognition,2018.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images Deep March- ing Cubes: Learning Explicit Surface Representations, IEEE/CVF Conference on Computer Vision and Pattern Recognition,2018

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This paper cites Deep Mesh Reconstruction From Single RGB Images via Topology Modification Networks, IEEE/CVF International Conference on Computer Vision (ICCV), 2020.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images Deep Mesh Reconstruction From Single RGB Images via Topology Modification Networks, IEEE/CVF International Conference on Computer Vision (ICCV), 2020

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Observation 3824ed54-8ef5-4f6b-8472-0ec72b5d1254 · outbound

This paper cites Pixel2Mesh: Generating 3D Mesh Models from Single RGB Images, In Proc.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images Pixel2Mesh: Generating 3D Mesh Models from Single RGB Images, In Proc

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This paper cites Differentiable Volumetric Rendering: Learning Implicit3DRepresentationsWithout3DSupervision,IEEE/CVFCon- ference on Computer Vision and Pattern Recognition (CVPR), 2020.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images Differentiable Volumetric Rendering: Learning Implicit3DRepresentationsWithout3DSupervision,IEEE/CVFCon- ference on Computer Vision and Pattern Recognition (CVPR), 2020

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This paper cites Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representations.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representations

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This paper cites Pix2Vox: Context-Aware 3D Reconstruction From Single and Multi-View Images, Inter- national Conference on Computer Vision (ICCV), IEEE, 2020.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images Pix2Vox: Context-Aware 3D Reconstruction From Single and Multi-View Images, Inter- national Conference on Computer Vision (ICCV), IEEE, 2020

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This paper cites Es- caping Plato’s Cave: 3D Shape From Adversarial Rendering, In- ternational Conference on Computer Vision (ICCV), IEEE, 2019.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images Es- caping Plato’s Cave: 3D Shape From Adversarial Rendering, In- ternational Conference on Computer Vision (ICCV), IEEE, 2019

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Observation 5eae8db1-32fb-48cd-a0e1-4f5fe8afa877 · outbound

This paper cites HoloGAN: Unsupervised learning of 3D representations from natural images, ICCV, 2019.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images HoloGAN: Unsupervised learning of 3D representations from natural images, ICCV, 2019

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This paper cites BlockGAN: Learning 3D Object-aware Scene Representations from Unlabelled Images.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images BlockGAN: Learning 3D Object-aware Scene Representations from Unlabelled Images

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This paper cites GIRAFFE: Representing ScenesasCompositionalGenerativeNeuralFeatureFields,IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR),.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images GIRAFFE: Representing ScenesasCompositionalGenerativeNeuralFeatureFields,IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR),

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CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images Demystifying MMD GANs

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CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images FastNeRF: High-Fidelity Neural Rendering at 200FPS

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CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenes

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CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images pixelNeRF: Neural Radiance Fields from One or Few Images

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This paper cites and Martin-Brualla, Ricardo and Snavely, Noah and Funkhouser, Thomas.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images and Martin-Brualla, Ricardo and Snavely, Noah and Funkhouser, Thomas

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This paper cites StylizedNeRF: Consistent 3D Scene Stylization as Stylized NeRF via 2D-3D Mutual Learning, IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images StylizedNeRF: Consistent 3D Scene Stylization as Stylized NeRF via 2D-3D Mutual Learning, IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022

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This paper cites Liu and T.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images Liu and T

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CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images Image quality assessment: From error visibility to structural similarity, 2013

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This paper cites HeadNeRF: A Real-time NeRF-based Parametric Head Model.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images HeadNeRF: A Real-time NeRF-based Parametric Head Model

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CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images GRAM: Generative Radiance Manifolds for 3D-Aware Image Generation

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CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images Unresolved cited work

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This paper cites StyleNeRF: A Style-based 3D-Aware Generator for High-resolution Image Synthesis.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images StyleNeRF: A Style-based 3D-Aware Generator for High-resolution Image Synthesis

Reference 53

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Observation 392856f1-5df3-4fce-9d34-452846e393b0 · outbound

This paper cites CLIP-NeRF: Text-and-Image Driven Manipulation of Neural Radiance Fields.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images CLIP-NeRF: Text-and-Image Driven Manipulation of Neural Radiance Fields

Reference 59

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Observation 23743f28-c0f0-4fe6-bb3a-7ff28871967b · outbound

This paper cites Generative Adversarial Networks.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images Generative Adversarial Networks

Reference 2014

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Observation 9c432ae6-8ae4-4cd0-9be2-84c3c7a03df4 · outbound

This paper cites Conditional Image Synthesis With Auxiliary Classifier GANs.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images Conditional Image Synthesis With Auxiliary Classifier GANs

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-12T05:06:48.847338Z

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Observation 63592901-84ca-40e1-ba54-df3edd9c5620 · outbound

This paper cites an unresolved cited work.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images Unresolved cited work

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-12T05:06:48.938625Z

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Observation 746b3ff0-fb57-429a-846d-900f1ad2c1f6 · outbound

This paper cites an unresolved cited work.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images Unresolved cited work

Reference 2020

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Observation 5bd1e26d-47ca-401f-bfed-6db4c91a5bfd · outbound

This paper cites Advances in Neural Rendering.

CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images Advances in Neural Rendering

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-12T05:06:48.920197Z

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