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LightNet++

!!!New Repo.!!! EfficientNet.PyTorch: Concise, Modular, Human-friendly PyTorch implementation of EfficientNet with Pre-trained Weights

!!!New Repo.!!! MixNet-Pytorch: Concise, Modular, Human-friendly PyTorch implementation of MixNet with Pre-trained Weights

This repository contains the code (PyTorch-1.0+, W.I.P.) for: "LightNet++: Boosted Light-weighted Networks for Real-time Semantic Segmentation" by Huijun Liu.
LightNet++ is an advanced version of LightNet, which purpose to get more concise model design, smaller models, and better performance.

  • MobileNetV2Plus: Modified MobileNetV2 (backbone)[1,8] + DSASPPInPlaceABNBlock[2,3] + Parallel Bottleneck Channel-Spatial Attention Block (PBCSABlock)[6] + UnSharp Masking (USM) + Encoder-Decoder Arch.[3] + InplaceABN[4].

  • ShuffleNetV2Plus: Modified ShuffleNetV2 (backbone)[1,8] + DSASPPInPlaceABNBlock[2,3] + Parallel Bottleneck Channel-Spatial Attention Block (PBCSABlock)[6]+ UnSharp Masking (USM) + Encoder-Decoder Arch.[3] + InplaceABN[4].

  • MixSeg-MixBiFPN: Modified MixNet (backbone)[1,8] + MixBiFPNBlock[2,3] + Encoder-Decoder Arch.[3]

More about USM(Unsharp Mask)-Operator Block see Repo: SharpPeleeNet

Dependencies

Datasets for Autonomous Driving

Results

Results on Cityscapes (Pixel-level/Semantic Segmentation)

Model mIoU (S.S* Mixed Precision) Model Weight
MobileNetV2Plus X1.0 71.5314 (WIP) cityscapes_mobilenetv2plus_x1.0.pkl (14.3 MB)
ShuffleNetV2Plus X1.0 69.0885-72.5255 (WIP) cityscapes_shufflenetv2plus_x1.0.pkl (8.59 MB)
MixSeg+MixBiFPN ArchS 72.2321 (WIP) cityscapes_mixseg_archs_mixbifpn.pkl (16.4 MB)
  • S.S.: Single Scale (1024x2048)

Feature Visualization


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