List of useful data augmentation resources. You will find here some not common techniques, libraries, links to GitHub repos, papers, and others.
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Updated
Aug 14, 2024
List of useful data augmentation resources. You will find here some not common techniques, libraries, links to GitHub repos, papers, and others.
[CVPR 2020--Oral] CycleISP: Real Image Restoration via Improved Data Synthesis
Computer vision utils for Blender (generate instance annoatation, depth and 6D pose by one line code)
This repository collects papers for "A Survey on Knowledge Distillation of Large Language Models". We break down KD into Knowledge Elicitation and Distillation Algorithms, and explore the Skill & Vertical Distillation of LLMs.
[CVPR 2023] Label-Free Liver Tumor Segmentation
Coursera - RNN Programming Assignment: In this project, we will construct a speech dataset and implement an algorithm for trigger word detection (sometimes also called keyword detection, or wake word detection).
A data framework for music information retrieval focusing on electronic music.
Repository for the results of my master thesis, about the generation and evaluation of synthetic data using GANs
Apache NiFi Data Synthesizer
Source code for LDPTrace: Locally Differentially Private Trajectory Synthesis. VLDB 2023.
A data synthesizer for creating datasets of feet from a first-person perspective.
The Coastal Carbon Network Data Library: An open-source database featuring carbon data from tidal wetlands around the world
[Preprint] Deformation-Recovery Diffusion Model (DRDM): Instance Deformation for Image Manipulation and Synthesis
Boosting Document Intelligence
Official implementaion of EMNLP 2022 paper "Generate, Discriminate, and Contrast: A Semi-Supervised Sentence Representation Learning Framework"
official code for Customizable Embodied Multi-modal Perturbations for SLAM Robustness Benchmarking
Code & data for ICLR 2024 spotlight paper: 🍯MUSTARD: Mastering Uniform Synthesis of Theorem and Proof Data
Synthesis data in YOLO format given background and object images
SynthShapes is a Python package for generating synthetic shapes in 3D, tailored for augmenting biomedical imaging training datasets.
Since the times of d'Alembert, Lagrange and Euler humans like to add fictitious dimensions to their real-world physical and mathematical problems. This art was perfected in the XX-th century by Heisenberg, Pauli and Dirac in their 'matrix mechanics'. In the XXI-st century we can contribute to this proud tradition too, we have computers! :)
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