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Bayesian Monocular Depth Refinement via Neural Radiance Fields

arXiv 2601.03869 ↗First posted 7 Jan 2026cs.CV cs.GR cs.LGcited by 0

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Abstract (arXiv)

Monocular depth estimation has applications in many fields, such as autonomous navigation and extended reality, making it an essential computer vision task. However, current methods often produce smooth depth maps that lack the fine geometric detail needed for accurate scene understanding. We propose MDENeRF, an iterative framework that refines monocular depth estimates using depth information from Neural Radiance Fields (NeRFs). MDENeRF consists of three components: (1) an initial monocular estimate for global structure, (2) a NeRF trained on perturbed viewpoints, with per-pixel uncertainty, and (3) Bayesian fusion of the noisy monocular and NeRF depths. We derive NeRF uncertainty from the volume rendering process to iteratively inject high-frequency fine details. Meanwhile, our monocular prior maintains global structure. We demonstrate improvements on key metrics and experiments using indoor scenes from the SUN RGB-D dataset.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 15 of its 21 references that are in the map. First posted on arXiv 7 Jan 2026.

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15 of 21 references.

References · 15

  1. 2022Instant Neural Graphics Primitives with a Multiresolution Hash Encodingcited by 3,723
  2. 2019Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfercited by 1,495
  3. 2014Depth Map Prediction from a Single Image using a Multi-Scale Deep Networkcited by 1,274
  4. 2016Unsupervised Monocular Depth Estimation with Left-Right Consistencycited by 820
  5. 2017Unsupervised Learning of Depth and Ego-Motion from Videocited by 782
  6. 2018Deep Ordinal Regression Network for Monocular Depth Estimationcited by 723
  7. 2020AdaBins: Depth Estimation using Adaptive Binscited by 601
  8. 2016Deeper Depth Prediction with Fully Convolutional Residual Networkscited by 403
  9. 2017End-to-End Learning of Geometry and Context for Deep Stereo Regressioncited by 360
  10. 2018Learning Depth with Convolutional Spatial Propagation Networkcited by 136
  11. 2014Deep Convolutional Neural Fields for Depth Estimation from a Single Imagecited by 106
  12. 2020Predicting Sharp and Accurate Occlusion Boundaries in Monocular Depth Estimation Using Displacement Fieldscited by 40
3 more
  1. 2023SCADE: NeRFs from Space Carving with Ambiguity-Aware Depth Estimatescited by 35
  2. 2022Multi-resolution Monocular Depth Map Fusion by Self-supervised Gradient-based Compositioncited by 8
  3. 2025The Fourth Monocular Depth Estimation Challengecited by 8

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