Lists (3)
Stars
Personalized Federated Learning with Moreau Envelopes (pFedMe) using Pytorch (NeurIPS 2020)
Heterogeneous Federated Learning: State-of-the-art and Research Challenges
Using Federated Learning to train the model in Semantic Communication in pytorch
TPAMI2023 & CVPR2022 - Generalizable Heterogeneous Federated Cross-Correlation and Instance Similarity Learning & Learn From Others and Be Yourself in Heterogeneous Federated Learning
A simple code base for multi-task dense prediction methods, supporting both multi-decoder and task-conditional models
[CVPR2024] FedHCA^2: Towards Hetero-Client Federated Multi-Task Learning
A user-friendly evaluation tool that encompasses all necessary components for boundary detection on PASCAL-Context and NYUD-v2 datasets.
[CVPRW 2023] "Many-Task Federated Learning: A New Problem Setting and A Simple Baseline" by Ruisi Cai, Xiaohan Chen, Shiwei Liu, Jayanth Srinivasa, Myungjin Lee, Ramana Kompella, Zhangyang Wang
Knowledge Distillation for Multi-task Learning (ECCV20 Workshops)
PyTorch implementation of Federated Learning with Non-IID Data, and federated learning algorithms, including FedAvg, FedProx.
1 min voice data can also be used to train a good TTS model! (few shot voice cloning)
A playbook for systematically maximizing the performance of deep learning models.
基于Pytorch框架的语义分割学习，FCN，UNet，DeepLab 基于VOC数据集。
A PyTorch Implementation of Federated Learning
RTSeg: Real-time Semantic Segmentation Comparative Study
Support PointRend, Fast_SCNN, HRNet, Deeplabv3_plus(xception, resnet, mobilenet), ContextNet, FPENet, DABNet, EdaNet, ENet, Espnetv2, RefineNet, UNet, DANet, HRNet, DFANet, HardNet, LedNet, OCNet, …
MobileNets-SSD/SSDLite on VOC/BDD100K Datasets
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
这是一个mobilenet-ssd-keras的源码，可以用于训练自己的轻量级ssd模型。
MobileNetV3 SSD的简洁版本
MobileNetV3-SSD for object detection and implementation in PyTorch