# Hierarchical Opacity Propagation for Image Matting

arXiv: https://arxiv.org/abs/2004.03249 · HTML: https://mlsanity.com/paper/2004.03249/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 Apr 2020.

## Built on by (most cited first, 5 of 5)

- [Deep Image Matting: A Comprehensive Survey](https://mlsanity.com/paper/2304.04672/) (2023)
- [Multimodal Vision Transformers with Forced Attention for Behavior Analysis](https://mlsanity.com/paper/2212.03968/) (2022)
- [Trimap-guided Feature Mining and Fusion Network for Natural Image Matting](https://mlsanity.com/paper/2112.00510/) (2021)
- [Color-aware Deep Temporal Backdrop Duplex Matting System](https://mlsanity.com/paper/2306.02954/) (2023)
- [Automatic Portrait Video Matting via Context Motion Network](https://mlsanity.com/paper/2109.04598/) (2021)

## Abstract (arXiv)

Natural image matting is a fundamental problem in computational photography and computer vision. Deep neural networks have seen the surge of successful methods in natural image matting in recent years. In contrast to traditional propagation-based matting methods, some top-tier deep image matting approaches tend to perform propagation in the neural network implicitly. A novel structure for more direct alpha matte propagation between pixels is in demand. To this end, this paper presents a hierarchical opacity propagation (HOP) matting method, where the opacity information is propagated in the neighborhood of each point at different semantic levels. The hierarchical structure is based on one global and multiple local propagation blocks. With the HOP structure, every feature point pair in high-resolution feature maps will be connected based on the appearance of input image. We further propose a scale-insensitive positional encoding tailored for image matting to deal with the unfixed size of input image and introduce the random interpolation augmentation into image matting. Extensive experiments and ablation study show that HOP matting is capable of outperforming state-of-the-art matting methods.