# LEDNet: A Lightweight Encoder-Decoder Network for Real-Time Semantic Segmentation

arXiv: https://arxiv.org/abs/1905.02423 · HTML: https://mlsanity.com/paper/1905.02423/

## Key facts

- Cited by 50 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 May 2019.

## Built on by (most cited first, 30 of 50)

- [SeMask: Semantically Masked Transformers for Semantic Segmentation](https://mlsanity.com/paper/2112.12782/) (2021)
- [Enhanced Boundary Learning for Glass-like Object Segmentation](https://mlsanity.com/paper/2103.15734/) (2021)
- [Trans4Trans: Efficient Transformer for Transparent Object Segmentation to Help Visually Impaired People Navigate in the Real World](https://mlsanity.com/paper/2107.03172/) (2021)
- [Trans4Trans: Efficient Transformer for Transparent Object and Semantic Scene Segmentation in Real-World Navigation Assistance](https://mlsanity.com/paper/2108.09174/) (2021)
- [FBSNet: A Fast Bilateral Symmetrical Network for Real-Time Semantic Segmentation](https://mlsanity.com/paper/2109.00699/) (2021)
- [NanoNet: Real-Time Polyp Segmentation in Video Capsule Endoscopy and Colonoscopy](https://mlsanity.com/paper/2104.11138/) (2021)
- [Stage-Aware Feature Alignment Network for Real-Time Semantic Segmentation of Street Scenes](https://mlsanity.com/paper/2203.04031/) (2022)
- [CFPNet: Channel-wise Feature Pyramid for Real-Time Semantic Segmentation](https://mlsanity.com/paper/2103.12212/) (2021)
- [MSCFNet: A Lightweight Network With Multi-Scale Context Fusion for Real-Time Semantic Segmentation](https://mlsanity.com/paper/2103.13044/) (2021)
- [Computation-efficient Deep Learning for Computer Vision: A Survey](https://mlsanity.com/paper/2308.13998/) (2023)
- [Segmenting Transparent Object in the Wild with Transformer](https://mlsanity.com/paper/2101.08461/) (2021)
- [Lightweight Real-time Semantic Segmentation Network with Efficient Transformer and CNN](https://mlsanity.com/paper/2302.10484/) (2023)
- [CFPNet-M: A Light-Weight Encoder-Decoder Based Network for Multimodal Biomedical Image Real-Time Segmentation](https://mlsanity.com/paper/2105.04075/) (2021)
- [Delta Distillation for Efficient Video Processing](https://mlsanity.com/paper/2203.09594/) (2022)
- [DRAW: Defending Camera-shooted RAW against Image Manipulation](https://mlsanity.com/paper/2307.16418/) (2023)
- [Enabling Resource-efficient AIoT System with Cross-level Optimization: A survey](https://mlsanity.com/paper/2309.15467/) (2023)
- [Semantic Scene Segmentation for Robotics Applications](https://mlsanity.com/paper/2108.11128/) (2021)
- [On Efficient Real-Time Semantic Segmentation: A Survey](https://mlsanity.com/paper/2206.08605/) (2022)
- [HUPE: Heuristic Underwater Perceptual Enhancement with Semantic Collaborative Learning](https://mlsanity.com/paper/2411.18296/) (2024)
- [Anomaly Detection of Defect using Energy of Point Pattern Features within Random Finite Set Framework](https://mlsanity.com/paper/2108.12159/) (2021)
- [Soft labelling for semantic segmentation: Bringing coherence to label down-sampling](https://mlsanity.com/paper/2302.13961/) (2023)
- [eWaSR -- an embedded-compute-ready maritime obstacle detection network](https://mlsanity.com/paper/2304.11249/) (2023)
- [MINet: Multi-scale Interactive Network for Real-time Salient Object Detection of Strip Steel Surface Defects](https://mlsanity.com/paper/2405.16096/) (2024)
- [HAFormer: Unleashing the Power of Hierarchy-Aware Features for Lightweight Semantic Segmentation](https://mlsanity.com/paper/2407.07441/) (2024)
- [LightLayers: Parameter Efficient Dense and Convolutional Layers for Image Classification](https://mlsanity.com/paper/2101.02268/) (2021)
- [Real-Time Monocular Human Depth Estimation and Segmentation on Embedded Systems](https://mlsanity.com/paper/2108.10506/) (2021)
- [Deep Multi-Branch Aggregation Network for Real-Time Semantic Segmentation in Street Scenes](https://mlsanity.com/paper/2203.04037/) (2022)
- [LGPS: A Lightweight GAN-Based Approach for Polyp Segmentation in Colonoscopy Images](https://mlsanity.com/paper/2503.18294/) (2025)
- [S2-FPN: Scale-ware Strip Attention Guided Feature Pyramid Network for Real-time Semantic Segmentation](https://mlsanity.com/paper/2206.07298/) (2022)
- [Cross-CBAM: A Lightweight network for Scene Segmentation](https://mlsanity.com/paper/2306.02306/) (2023)

## Abstract (arXiv)

The extensive computational burden limits the usage of CNNs in mobile devices for dense estimation tasks. In this paper, we present a lightweight network to address this problem,namely LEDNet, which employs an asymmetric encoder-decoder architecture for the task of real-time semantic segmentation.More specifically, the encoder adopts a ResNet as backbone network, where two new operations, channel split and shuffle, are utilized in each residual block to greatly reduce computation cost while maintaining higher segmentation accuracy. On the other hand, an attention pyramid network (APN) is employed in the decoder to further lighten the entire network complexity. Our model has less than 1M parameters,and is able to run at over 71 FPS in a single GTX 1080Ti GPU. The comprehensive experiments demonstrate that our approach achieves state-of-the-art results in terms of speed and accuracy trade-off on CityScapes dataset.