# Freq-DP Net: A Dual-Branch Network for Fence Removal using Dual-Pixel and Fourier Priors

arXiv: https://arxiv.org/abs/2602.14226 · HTML: https://mlsanity.com/paper/2602.14226/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 15 of its 24 references that are in the map.
- First posted on arXiv 15 Feb 2026.

## Builds on (most cited first, 15 of 15)

- [U-Net: Convolutional Networks for Biomedical Image Segmentation](https://mlsanity.com/paper/1505.04597/) (2015)
- [Restormer: Efficient Transformer for High-Resolution Image Restoration](https://mlsanity.com/paper/2111.09881/) (2021)
- [Resolution-robust Large Mask Inpainting with Fourier Convolutions](https://mlsanity.com/paper/2109.07161/) (2021)
- [Pyramid Stereo Matching Network](https://mlsanity.com/paper/1803.08669/) (2018)
- [Defocus Deblurring Using Dual-Pixel Data](https://mlsanity.com/paper/2005.00305/) (2020)
- [Robust Object Detection under Occlusion with Context-Aware CompositionalNets](https://mlsanity.com/paper/2005.11643/) (2020)
- [Learning Single Camera Depth Estimation using Dual-Pixels](https://mlsanity.com/paper/1904.05822/) (2019)
- [Dual Pixel Exploration: Simultaneous Depth Estimation and Image Restoration](https://mlsanity.com/paper/2012.00301/) (2020)
- [Defocus Map Estimation and Deblurring from a Single Dual-Pixel Image](https://mlsanity.com/paper/2110.05655/) (2021)
- [Learning to See Through Obstructions with Layered Decomposition](https://mlsanity.com/paper/2008.04902/) (2020)
- [Stereo image de-fencing using smartphones](https://mlsanity.com/paper/1612.01323/) (2016)
- [Accurate and efficient video de-fencing using convolutional neural networks and temporal information](https://mlsanity.com/paper/1806.10781/) (2018)
- [Robotic Occlusion Reasoning for Efficient Object Existence Prediction](https://mlsanity.com/paper/2107.12095/) (2021)
- [Efficient Flow-Guided Multi-frame De-fencing](https://mlsanity.com/paper/2301.10759/) (2023)
- [Instruct2See: Learning to Remove Any Obstructions Across Distributions](https://mlsanity.com/paper/2505.17649/) (2025)

## Abstract (arXiv)

Removing fence occlusions from single images is a challenging task that degrades visual quality and limits downstream computer vision applications. Existing methods often fail on static scenes or require motion cues from multiple frames. To overcome these limitations, we introduce the first framework to leverage dual-pixel (DP) sensors for this problem. We propose Freq-DP Net, a novel dual-branch network that fuses two complementary priors: a geometric prior from defocus disparity, modeled using an explicit cost volume, and a structural prior of the fence's global pattern, learned via Fast Fourier Convolution (FFC). An attention mechanism intelligently merges these cues for highly accurate fence segmentation. To validate our approach, we build and release a diverse benchmark with different fence varieties. Experiments demonstrate that our method significantly outperforms strong general-purpose baselines, establishing a new state-of-the-art for single-image, DP-based fence removal.