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EGFormer: Enhancing Group Attention for Off-Road Semantic Segmentation via Transition-Aware Refinement

Official implementation of "EGFormer: Enhancing Group Attention for Off-Road Semantic Segmentation via Transition-Aware Refinement".


Overview

EGFormer is an off-road semantic segmentation framework designed to improve boundary-aware perception in unstructured outdoor environments.
It introduces an edge-guided refinement strategy to better handle ambiguous transitions between terrain, vegetation, obstacles, and drivable regions.


Highlights

  • Edge-guided refinement for ambiguous off-road boundaries
  • Transformer-based semantic segmentation architecture
  • Robust to noisy labels and unclear class boundaries
  • Support for RUGD and RELLIS-3D datasets
  • MMSegmentation-based training and evaluation pipeline
  • ROS support for real-world robotic perception

Framework

Overall architecture of EGFormer.


Dataset Preparation

Supported Datasets

  • RUGD
  • RELLIS-3D

The dataset should be organized as follows:

EGFormer
├── data
│   ├── rellis
│   │   ├── test.txt
│   │   ├── train.txt
│   │   ├── val.txt
│   │   ├── annotation
│   │   │   ├── 00000
│   │   │   ├── 00001
│   │   │   ├── 00002
│   │   │   ├── 00003
│   │   │   └── 00004
│   │   └── image
│   │       ├── 00000
│   │       ├── 00001
│   │       ├── 00002
│   │       ├── 00003
│   │       └── 00004
│   │
│   └── rugd
│       ├── test_ours.txt
│       ├── test.txt
│       ├── train_ours.txt
│       ├── train.txt
│       ├── val_ours.txt
│       ├── val.txt
│       ├── RUGD_annotations
│       │   ├── creek
│       │   ├── park-1
│       │   ├── park-2
│       │   ├── park-8
│       │   ├── trail-1
│       │   ├── trail-3
│       │   ├── trail-7
│       │   ├── trail-9
│       │   ├── trail-15
│       │   └── village
│       └── RUGD_frames-with-annotations
│           ├── creek
│           ├── park-1
│           ├── park-2
│           ├── park-8
│           ├── trail-1
│           ├── trail-3
│           ├── trail-7
│           ├── trail-9
│           ├── trail-15
│           └── village
│
├── configs
├── tools
└── ...

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Enhancing Group Attention for Off-Road Semantic Segmentation via Transition-Aware Refinement (IEEE SPL 2026)

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