PyTorch implementation of Fast AutoAugment for Time Series
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Updated
Jun 19, 2024 - Python
PyTorch implementation of Fast AutoAugment for Time Series
Point Cloud Upsampling with Kernel Point Representation and Deformation
Implementation of DeepMind's Deep Generative Model of Radar (DGMR) https://arxiv.org/abs/2104.00954
👁️ 🖼️ 🔥PyTorch Toolbox for Image Quality Assessment, including LPIPS, FID, NIQE, NRQM(Ma), MUSIQ, TOPIQ, NIMA, DBCNN, BRISQUE, PI and more...
Benchmark of federated learning. Dedicated to the community. 🤗
Translate manga/image 一键翻译各类图片内文字 https://cotrans.touhou.ai/
CRA-PCN: Point Cloud Completion with Intra- and Inter-level Cross-Resolution Transformers
LibCity: An Open Library for Urban Spatial-temporal Data Mining
Detection of cerebral microbleeds using deep learning method consisting of 2 steps: initial candidate detection and candidate discrimination using a student-teacher network.
The official code of "CSTA: CNN-based Spatiotemporal Attention for Video Summarization"
Pytorch implementation of projected gradient descent (PGD) adversarial noise attack
Simple model creation for time series classification in Pytorch
PyTorch implementation of the Hessian-free optimizer
Guided Interpretable Facial Expression Recognition via Spatial Action Unit Cues
Source code for paper: https://ieeexplore.ieee.org/abstract/document/9816283
Really simple unofficial PyTorch implementation of the InfiniAttention paper (https://arxiv.org/pdf/2404.07143).
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