Differentiable Data Augmentation with Kornia
In this paper we present a review of the Kornia differentiable data augmentation (DDA) module for both for spatial (2D) and volumetric (3D) tensors. This module leverages differentiable computer vision solutions from Kornia, with an aim of integrating data augmentation (DA) pipelines and strategies to existing PyTorch components (e.g. autograd for differentiability, optim for optimization). In addition, we provide a benchmark comparing different DA frameworks and a short review for a number of approaches that make use of Kornia DDA.
Code (1)
Tasks
Image AugmentationImage Manipulationimage smoothingSimilar Papers 제목 키워드 기반
Kornia: an Open Source Differentiable Computer Vision Library for PyTorch
This work presents Kornia -- an open source computer vision library which consists of a set of differentiable routines and modules to solve generic computer vision problems. The package uses PyTorch as its main backend b…
Camera CalibrationData AugmentationEdge DetectionImage Augmentation+9A survey on Kornia: an Open Source Differentiable Computer Vision Library for PyTorch
This work presents Kornia, an open source computer vision library built upon a set of differentiable routines and modules that aims to solve generic computer vision problems. The package uses PyTorch as its main backend,…
Camera CalibrationData AugmentationEdge DetectionImage Augmentation+1Kornia-rs: A Low-Level 3D Computer Vision Library In Rust
We present \textit{kornia-rs}, a high-performance 3D computer vision library written entirely in native Rust, designed for safety-critical and real-time applications. Unlike C++-based libraries like OpenCV or wrapper-bas…
Direct Differentiable Augmentation Search
Data augmentation has been an indispensable tool to improve the performance of deep neural networks, however the augmentation can hardly transfer among different tasks and datasets. Consequently, a recent trend is to ado…
AutoMLData AugmentationGPUimage-classification+4CADDA: Class-wise Automatic Differentiable Data Augmentation for EEG Signals
Data augmentation is a key element of deep learning pipelines, as it informs the network during training about transformations of the input data that keep the label unchanged. Manually finding adequate augmentation metho…
Data AugmentationEEGElectroencephalogram (EEG)