https://github.com/lufficc/dpnet
Data Priming Network for Automatic Check-Out - ACMMM 2019
https://github.com/lufficc/dpnet
acmmm2019 dpnet pytorch
Last synced: 6 months ago
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Data Priming Network for Automatic Check-Out - ACMMM 2019
- Host: GitHub
- URL: https://github.com/lufficc/dpnet
- Owner: lufficc
- Created: 2019-08-01T15:01:10.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2019-09-09T14:35:50.000Z (over 5 years ago)
- Last Synced: 2023-10-20T21:20:28.652Z (over 1 year ago)
- Topics: acmmm2019, dpnet, pytorch
- Homepage:
- Size: 1.98 MB
- Stars: 26
- Watchers: 8
- Forks: 2
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
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README
# Data Priming Network for Automatic Check-Out
Introduction
-----------------
This paper was accepted to ACM MM 2019.
This repository implements DPNet ([Data Priming Network for Automatic Check-Out](https://arxiv.org/abs/1904.04978)) using PyTorch 1.0.1 . This implementation is heavily influenced by the project [maskrcnn-benchmark](https://github.com/facebookresearch/maskrcnn-benchmark).
We propose a new data priming method
to solve the domain adaptation problem. Specifically, we first use
pre-augmentation data priming, in which we remove distracting
background from the training images using the coarse-to-fine strategy and select images with realistic view angles by the pose pruning
method. In the post-augmentation step, we train a data priming
network using detection and counting collaborative learning, and
select more reliable images from testing data to fine-tune the final
visual item tallying network.
## Code
Source code and more details are available [here](https://isrc.iscas.ac.cn/gitlab/research/acm-mm-2019-ACO).
## Results
| level | method | cAcc | mCIoU | ACD | mCCD | mAP50 | mmAP |
| ---: | ---: | ---: | ---: | ---: | ---: | ---: | ---: |
| easy | Syn+Render (DPNet) | 90.32% | 97.87% | 0.15 | 0.02 | 98.6% | 83.07% |
| medium | Syn+Render (DPNet) | 80.68% | 97.38% | 0.32 | 0.03 | 98.07% | 77.25% |
| hard | Syn+Render (DPNet) | 70.76% | 97.04% | 0.53 | 0.03 | 97.76% | 74.95% |
| averaged | Syn+Render (DPNet) | 80.51% | 97.33% | 0.34 | 0.03 | 97.91% | 77.04% |
## Model ZOO
| level | method | cAcc | model |
| ---: | ---: | ---: | ---: |
| averaged | Render (DPNet) | 77.91% | [download](https://github.com/lufficc/DPNet/releases/download/0.1/render_finetune.pth) |
| averaged | Syn+Render (DPNet) | 80.51% | [download](https://github.com/lufficc/DPNet/releases/download/0.1/syn_render_finetune.pth) |
## Citations
Please cite this project in your publications if it helps your research.
```
@inproceedings{li2019data,
title={Data Priming Network for Automatic Check-Out},
author={Li, Congcong and Du, Dawei and Zhang, Libo and Luo, Tiejian and Wu, Yanjun and Tian, Qi and Wen, Longyin and Lyu, Siwei},
booktitle={2019 ACM Multimedia Conference on Multimedia Conference},
year={2019},
organization={ACM}
}
```