mlsanityData to 14 Oct 2026

NieR: Normal-Based Lighting Scene Rendering

arXiv 2405.13097 ↗First posted 21 May 2024cs.CVcited by 0

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Abstract (arXiv)

In real-world road scenes, diverse material properties lead to complex light reflection phenomena, making accurate color reproduction crucial for enhancing the realism and safety of simulated driving environments. However, existing methods often struggle to capture the full spectrum of lighting effects, particularly in dynamic scenarios where viewpoint changes induce significant material color variations. To address this challenge, we introduce NieR (Normal-Based Lighting Scene Rendering), a novel framework that takes into account the nuances of light reflection on diverse material surfaces, leading to more precise rendering. To simulate the lighting synthesis process, we present the LD (Light Decomposition) module, which captures the lighting reflection characteristics on surfaces. Furthermore, to address dynamic lighting scenes, we propose the HNGD (Hierarchical Normal Gradient Densification) module to overcome the limitations of sparse Gaussian representation. Specifically, we dynamically adjust the Gaussian density based on normal gradients. Experimental evaluations demonstrate that our method outperforms state-of-the-art (SOTA) methods in terms of visual quality and exhibits significant advantages in performance indicators. Codes are available at https://wanghongsheng01.github.io/NieR/.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 17 of its 42 references that are in the map. First posted on arXiv 21 May 2024.

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17 of 42 references.

References · 17

  1. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,177
  2. 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,226
  3. 2022Instant Neural Graphics Primitives with a Multiresolution Hash Encodingcited by 3,723
  4. 2021Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fieldscited by 2,032
  5. 2021Plenoxels: Radiance Fields without Neural Networkscited by 1,613
  6. 2020Nerfies: Deformable Neural Radiance Fieldscited by 1,198
  7. 20234D Gaussian Splatting for Real-Time Dynamic Scene Renderingcited by 1,157
  8. 2023GaussianShader: 3D Gaussian Splatting with Shading Functions for Reflective Surfacescited by 252
  9. 2024A Survey on 3D Gaussian Splattingcited by 224
  10. 2022Modeling Indirect Illumination for Inverse Renderingcited by 168
  11. 2023Relightable 3D Gaussians: Realistic Point Cloud Relighting with BRDF Decomposition and Ray Tracingcited by 142
  12. 2023NeRF-DS: Neural Radiance Fields for Dynamic Specular Objectscited by 111
5 more
  1. 2024Deblurring 3D Gaussian Splattingcited by 66
  2. 2022HDR-Plenoxels: Self-Calibrating High Dynamic Range Radiance Fieldscited by 40
  3. 2023Human101: Training 100+FPS Human Gaussians in 100s from 1 Viewcited by 32
  4. 2018Gaussian Material Synthesiscited by 6
  5. 2022VM-NeRF: Tackling Sparsity in NeRF with View Morphingcited by 6

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