# Unified Depth Prediction and Intrinsic Image Decomposition from a Single Image via Joint Convolutional Neural Fields

arXiv: https://arxiv.org/abs/1603.06359 · HTML: https://mlsanity.com/paper/1603.06359/

## Key facts

- Cited by 17 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Mar 2016.

## Built on by (most cited first, 17 of 17)

- [StructDepth: Leveraging the structural regularities for self-supervised indoor depth estimation](https://mlsanity.com/paper/2108.08574/) (2021)
- [Single Image Depth Estimation: An Overview](https://mlsanity.com/paper/2104.06456/) (2021)
- [DaRF: Boosting Radiance Fields from Sparse Inputs with Monocular Depth Adaptation](https://mlsanity.com/paper/2305.19201/) (2023)
- [360 Depth Estimation in the Wild -- The Depth360 Dataset and the SegFuse Network](https://mlsanity.com/paper/2202.08010/) (2022)
- [Skeleton-Based Mutually Assisted Interacted Object Localization and Human Action Recognition](https://mlsanity.com/paper/2110.14994/) (2021)
- [DAG: Depth-Aware Guidance with Denoising Diffusion Probabilistic Models](https://mlsanity.com/paper/2212.08861/) (2022)
- [Semi-Supervised Learning with Mutual Distillation for Monocular Depth Estimation](https://mlsanity.com/paper/2203.09737/) (2022)
- [Generative Portrait Shadow Removal](https://mlsanity.com/paper/2410.05525/) (2024)
- [PRISM: A Unified Framework for Photorealistic Reconstruction and Intrinsic Scene Modeling](https://mlsanity.com/paper/2504.14219/) (2025)
- [Discriminative feature encoding for intrinsic image decomposition](https://mlsanity.com/paper/2209.12155/) (2022)
- [A Weakly-Supervised Depth Estimation Network Using Attention Mechanism](https://mlsanity.com/paper/2107.04819/) (2021)
- [Light Robust Monocular Depth Estimation For Outdoor Environment Via Monochrome And Color Camera Fusion](https://mlsanity.com/paper/2202.12108/) (2022)
- [MaskingDepth: Masked Consistency Regularization for Semi-supervised Monocular Depth Estimation](https://mlsanity.com/paper/2212.10806/) (2022)
- [Intrinsic Image Decomposition Using Point Cloud Representation](https://mlsanity.com/paper/2307.10924/) (2023)
- [Intrinsic Image Decomposition for Robust Self-supervised Monocular Depth Estimation on Reflective Surfaces](https://mlsanity.com/paper/2503.22209/) (2025)
- [EndoGMDE: Generalizable Monocular Depth Estimation with Mixture of Low-Rank Experts for Diverse Endoscopic Scenes](https://mlsanity.com/paper/2509.01206/) (2025)
- [CoGE: Sim-to-Real Online Geometric Estimation for Monocular Colonoscopy](https://mlsanity.com/paper/2605.13038/) (2026)

## Abstract (arXiv)

We present a method for jointly predicting a depth map and intrinsic images from single-image input. The two tasks are formulated in a synergistic manner through a joint conditional random field (CRF) that is solved using a novel convolutional neural network (CNN) architecture, called the joint convolutional neural field (JCNF) model. Tailored to our joint estimation problem, JCNF differs from previous CNNs in its sharing of convolutional activations and layers between networks for each task, its inference in the gradient domain where there exists greater correlation between depth and intrinsic images, and the incorporation of a gradient scale network that learns the confidence of estimated gradients in order to effectively balance them in the solution. This approach is shown to surpass state-of-the-art methods both on single-image depth estimation and on intrinsic image decomposition.