---
license: mit
tags:
  - segmentation
  - semantic-segmentation
  - segformer
  - sports
  - advertising-boards
  - mmsegmentation
---

# Advertising Panel Segmentation — SegFormer

Semantic segmentation models for detecting advertising LED boards in sports broadcasting footage.

## Dataset
- **967 images** at 1920x1080 from sports highlights
- **Manually annotated** via CVAT.ai with polygon annotations
- **Binary segmentation**: background (0) vs advertising board (1)
- **Split**: Train 672 / Val 149 / Test 146

## Models

| Experiment | Model | Augmentation | mIoU | Board IoU | Dice | Precision | Recall |
|---|---|---|---|---|---|---|---|
| Exp0 | SegFormer-B0 | Standard | 87.15% | 76.28% | 86.55% | 84.13% | 89.10% |
| Exp1 | SegFormer-B1 | Standard | 84.29% | 71.12% | 83.12% | 79.26% | 87.39% |
| **Exp2** | **SegFormer-B1** | **Sport-specific** | **87.26%** | **76.45%** | **86.66%** | **85.76%** | **87.57%** |
| Exp3-opt1 | SegFormer-B1 | Sport-specific reduced + LR 3e-5 + channels=512 | 84.58% | 71.68% | 83.51% | 78.66% | 88.99% |
| Exp3-opt2 | SegFormer-B1 | Sport-specific reduced + LR 3e-5 + channels=256 | 84.92% | 72.26% | 83.90% | 80.40% | 87.71% |
| Exp3-opt3 | SegFormer-B1 | Sport-specific + drop_path=0.15 | 86.42% | 74.99% | 85.71% | 82.25% | 89.47% |

Best model: **Exp2 - SegFormer-B1 Augmented** (`models/exp2_segformer_b1_augmented/best_mIoU_iter_14000.pth`)

## Detailed Results

### Exp0 - SegFormer-B0 Baseline
- Best checkpoint: best_mIoU_iter_18000.pth
- mIoU: 87.15% | Board IoU: 76.28% | Dice: 86.55% | Precision: 84.13% | Recall: 89.10%

### Exp1 - SegFormer-B1 Standard
- Best checkpoint: best_mIoU_iter_10000.pth
- mIoU: 84.29% | Board IoU: 71.12% | Dice: 83.12% | Precision: 79.26% | Recall: 87.39%

### Exp2 - SegFormer-B1 Augmented ⭐ Best
- Best checkpoint: best_mIoU_iter_14000.pth
- mIoU: 87.26% | Board IoU: 76.45% | Dice: 86.66% | Precision: 85.76% | Recall: 87.57%

### Exp3 - SegFormer-B1 Optimized1
- Best checkpoint: best_mIoU_iter_14000.pth
- mIoU: 84.58% | Board IoU: 71.68% | Dice: 83.51% | Precision: 78.66% | Recall: 88.99%

### Exp3 - SegFormer-B1 Optimized2
- Best checkpoint: best_mIoU_iter_12000.pth
- mIoU: 84.92% | Board IoU: 72.26% | Dice: 83.90% | Precision: 80.40% | Recall: 87.71%

### Exp3 - SegFormer-B1 Optimized3
- Best checkpoint: best_mIoU_iter_18000.pth
- mIoU: 86.42% | Board IoU: 74.99% | Dice: 85.71% | Precision: 82.25% | Recall: 89.47%

## Framework
- PyTorch 2.4.1
- MMSegmentation 1.2.2
- mmcv 2.2.0

## Repository Structure
```
models/
  exp0_segformer_b0_baseline/best_mIoU_iter_18000.pth
  exp1_segformer_b1_standard/best_mIoU_iter_10000.pth
  exp2_segformer_b1_augmented/best_mIoU_iter_14000.pth
  exp3_segformer_b1_optimized/best_mIoU_iter_14000.pth
  exp3_segformer_b1_optimized2/best_mIoU_iter_12000.pth
  exp3_segformer_b1_optimized3/best_mIoU_iter_18000.pth
dataset/
  processed.zip  (967 images + masks, train/val/test split)
```

## GitHub
https://github.com/ilMassy/advertising-panel-segmentation