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# APD
**Adaptive Perspective Distillation for Semantic Segmentation**

Zhuotao Tian*; Pengguang Chen*; Xin Lai; Li Jiang; Shu Liu; Hengshuang Zhao; Bei Yu; Ming-Chang Yang; Jiaya Jia

This project provides an implementation for the TPAMI 2022 paper "[Adaptive Perspective Distillation for Semantic Segmentation](https://ieeexplore.ieee.org/document/9736597)"

## Environment

We verify our code on
* 4x3090 GPUs
* CUDA 11.1
* python 3.9
* torch 1.12.1
* torchvision 0.13.1

Other similar envirouments should also work properly.

## Installation

```
git clone [email protected]:akuxcw/APD.git
cd APD/
```

## Results

| Dataset | Student | Teacher | Baseline | Ours |
|----------------|------------|-------------|----------|-------|
| ade20k | PSPNet-R18 | PSPNet-R101 | 37.19 | 39.25 |
| cityscapes | PSPNet-R18 | PSPNet-R101 | 74.15 | 75.68 |
| pascal context | PSPNet-R18 | PSPNet-R101 | 42.29 | 43.96 |



## Training

Use the following command to train PSPNet-R18 on ade20k with APD
```
bash ./tool/train.sh ade20k release_psp18_psp101
```

## <a name="Citation"></a>Citation

Please consider citing ReviewKD in your publications if it helps your research.

```bib
@article{APD,
author = {Zhuotao Tian and
Pengguang Chen and
Xin Lai and
Li Jiang and
Shu Liu and
Hengshuang Zhao and
Bei Yu and
Ming{-}Chang Yang and
Jiaya Jia},
title = {Adaptive Perspective Distillation for Semantic Segmentation},
journal = {{IEEE} Trans. Pattern Anal. Mach. Intell.},
pages = {1372--1387},
year = {2023}
}}
```

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