mlsanityData to 14 Oct 2026

Noise-NeRF: Hide Information in Neural Radiance Fields using Trainable Noise

arXiv 2401.01216 ↗First posted 2 Jan 2024cs.CVcited by 4

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Abstract (arXiv)

Neural Radiance Field (NeRF) has been proposed as an innovative advancement in 3D reconstruction techniques. However, little research has been conducted on the issues of information confidentiality and security to NeRF, such as steganography. Existing NeRF steganography solutions have shortcomings in low steganography quality, model weight damage, and limited amount of steganographic information. This paper proposes Noise-NeRF, a novel NeRF steganography method employing Adaptive Pixel Selection strategy and Pixel Perturbation strategy to improve the quality and efficiency of steganography via trainable noise. Extensive experiments validate the state-of-the-art performances of Noise-NeRF on both steganography quality and rendering quality, as well as effectiveness in super-resolution image steganography.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 29 of its 44 references that are in the map. First posted on arXiv 2 Jan 2024.

Builds on

29 of 44 references.

References · 29

  1. 2017Attention Is All You Needcited by 60,361
  2. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,177
  3. 2017Towards Deep Learning Models Resistant to Adversarial Attackscited by 6,415
  4. 2018A Style-Based Generator Architecture for Generative Adversarial Networkscited by 6,013
  5. 2022Instant Neural Graphics Primitives with a Multiresolution Hash Encodingcited by 3,723
  6. 2016Towards Evaluating the Robustness of Neural Networkscited by 2,998
  7. 2017Progressive Growing of GANs for Improved Quality, Stability, and Variationcited by 2,988
  8. 2021Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fieldscited by 2,032
  9. 2021Plenoxels: Radiance Fields without Neural Networkscited by 1,613
  10. 2020pixelNeRF: Neural Radiance Fields from One or Few Imagescited by 1,584
  11. 2022TensoRF: Tensorial Radiance Fieldscited by 1,280
  12. 2022Block-NeRF: Scalable Large Scene Neural View Synthesiscited by 724
17 more
  1. 2021IBRNet: Learning Multi-View Image-Based Renderingcited by 703
  2. 2019Local Light Field Fusion: Practical View Synthesis with Prescriptive Sampling Guidelinescited by 672
  3. 2023Nerfstudio: A Modular Framework for Neural Radiance Field Developmentcited by 600
  4. 2018HiDDeN: Hiding Data With Deep Networkscited by 397
  5. 2018Recovering Realistic Texture in Image Super-resolution by Deep Spatial Feature Transformcited by 371
  6. 2016OctNet: Learning Deep 3D Representations at High Resolutionscited by 342
  7. 2022Rodin: A Generative Model for Sculpting 3D Digital Avatars Using Diffusioncited by 309
  8. 2023SINE: Semantic-driven Image-based NeRF Editing with Prior-guided Editing Fieldcited by 94
  9. 2023SeaThru-NeRF: Neural Radiance Fields in Scattering Mediacited by 75
  10. 2023NeO 360: Neural Fields for Sparse View Synthesis of Outdoor Scenescited by 53
  11. 2023CopyRNeRF: Protecting the CopyRight of Neural Radiance Fieldscited by 34
  12. 2022StegaNeRF: Embedding Invisible Information within Neural Radiance Fieldscited by 32
  13. 2018Distributionally Adversarial Attackcited by 26
  14. 2023Local 3D Editing via 3D Distillation of CLIP Knowledgecited by 20
  15. 2023General Neural Gauge Fieldscited by 12
  16. 2021Embedding Novel Views in a Single JPEG Imagecited by 10
  17. 2023Targeted Adversarial Attacks on Generalizable Neural Radiance Fieldscited by 10

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Cited by year

Citing papers per year: 2024: 4.

4 papers.

  1. 2024GS-Hider: Hiding Messages into 3D Gaussian Splattingcited by 26
  2. 2024IPA-NeRF: Illusory Poisoning Attack Against Neural Radiance Fieldscited by 5
  3. 2024Proactive Schemes: A Survey of Adversarial Attacks for Social Goodcited by 2
  4. 2024StegaINR4MIH: steganography by implicit neural representation for multi-image hidingcited by 0