常用的语义分割架构结构综述以及代码复现
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation
PyTorch implementation of over 30 realtime semantic segmentations models, e.g. BiSeNetv1, BiSeNetv2, CGNet, ContextNet, DABNet, DDRNet, EDANet, ENet, ERFNet, ESPNet, ESPNetv2, FastSCNN, ICNet, LEDNet, LinkNet, PP-LiteSeg, SegNet, ShelfNet, STDC, SwiftNet, and support knowledge distillation, distributed training, Optuna etc.
An Ace of Spades 0.75 server based on PySnip.
Semantic segmentation task for ADE20k & cityscapse dataset, based on several models.
Pytorch implementation of "Learning Lightweight Lane Detection CNNs by Self Attention Distillation (ICCV 2019)"
Implementation of UNet by Tensorflow Lite. Semantic segmentation without using GPU with RaspberryPi + Python. In order to maximize the learning efficiency of the model, this learns only the "Person" class of VOC2012. And Comparison with ENet.
Lots of semantic image segmentation implementations in Tensorflow/Keras
Realtime Semantic Segmentation (ICNet) for Self-Driving Vehicles
Pytorch to train ENet of Cityscapes datasets and CamVid datasets nicely
ENet for 2D semantic segmentation in ScanNet
instance segmentation of lanes for autonomous driving
Implementation of ENet by chainer
TensorFlow implementation of ENet (Support for GPU/CPU mode, slimming of meta file and pb file generation) I added a correspondence to CPU mode and Freeze Graph, RaspberryPi correspondence to kwotsin/TensorFlow-ENet. Tensorflow 1.11.0
This repository provides two deep learning pipelines for real-time scene analysis in Euro Truck Simulator 2. The first solution utilizes LaneNet with an ENet backbone for lane detection alongside Yolo11n for object detection. The second solution employs YOLOPv2 to simultaneously detect lanes and vehicles.
🤖 Enable continual learning by reproducing the On-Policy Self-Distillation algorithm for robust and efficient fine-tuning with TRL-based code.
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