# Deep Adaptive Wavelet Network

arXiv: https://arxiv.org/abs/1912.05035 · HTML: https://mlsanity.com/paper/1912.05035/

## Key facts

- Cited by 16 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Dec 2019.

## Built on by (most cited first, 16 of 16)

- [WaveMix: A Resource-efficient Neural Network for Image Analysis](https://mlsanity.com/paper/2205.14375/) (2022)
- [LiftPool: Bidirectional ConvNet Pooling](https://mlsanity.com/paper/2104.00996/) (2021)
- [PointWavelet: Learning in Spectral Domain for 3D Point Cloud Analysis](https://mlsanity.com/paper/2302.05201/) (2023)
- [Learnable Discrete Wavelet Pooling (LDW-Pooling) For Convolutional Networks](https://mlsanity.com/paper/2109.06638/) (2021)
- [Wavelet Regularization Benefits Adversarial Training](https://mlsanity.com/paper/2206.03727/) (2022)
- [Trainable Wavelet Neural Network for Non-Stationary Signals](https://mlsanity.com/paper/2205.03355/) (2022)
- [Reliable Joint Segmentation of Retinal Edema Lesions in OCT Images](https://mlsanity.com/paper/2212.00330/) (2022)
- [Hierarchical Spherical CNNs with Lifting-based Adaptive Wavelets for Pooling and Unpooling](https://mlsanity.com/paper/2205.15571/) (2022)
- [Texture Classification Network Integrating Adaptive Wavelet Transform](https://mlsanity.com/paper/2404.05300/) (2024)
- [WCCNet: Wavelet-context Cooperative Network for Efficient Multispectral Pedestrian Detection](https://mlsanity.com/paper/2308.01042/) (2023)
- [Adaptive Wavelet Filters as Practical Texture Feature Amplifiers for Parkinson's Disease Screening in OCT](https://mlsanity.com/paper/2503.19292/) (2025)
- [Conceptualizing Multi-scale Wavelet Attention and Ray-based Encoding for Human-Object Interaction Detection](https://mlsanity.com/paper/2507.10977/) (2025)
- [LifWavNet: Lifting Wavelet-based Network for Non-contact ECG Reconstruction from Radar](https://mlsanity.com/paper/2510.27692/) (2025)
- [Tracking spatial temporal details in ultrasound long video via wavelet analysis and memory bank](https://mlsanity.com/paper/2512.15066/) (2025)
- [Motion-Guided Semantic Alignment with Negative Prompts for Zero-Shot Video Action Recognition](https://mlsanity.com/paper/2604.17062/) (2026)
- [Transversal Pooling Neural Networks](https://mlsanity.com/paper/2609.36237/) (2026)

## Abstract (arXiv)

Even though convolutional neural networks have become the method of choice in many fields of computer vision, they still lack interpretability and are usually designed manually in a cumbersome trial-and-error process. This paper aims at overcoming those limitations by proposing a deep neural network, which is designed in a systematic fashion and is interpretable, by integrating multiresolution analysis at the core of the deep neural network design. By using the lifting scheme, it is possible to generate a wavelet representation and design a network capable of learning wavelet coefficients in an end-to-end form. Compared to state-of-the-art architectures, the proposed model requires less hyper-parameter tuning and achieves competitive accuracy in image classification tasks