/TriTransNet

Primary LanguagePython

TriTransNet: RGB-D Salient Object Detection with a Triplet Transformer Embedding Network

The paper has been accepted by ACM MM2021. The details are in paper official

TriTransNet

Code

链接：https://pan.baidu.com/s/1veASJR08IqR3Q4tMMa6kFA 提取码：1xb2

google https://drive.google.com/file/d/1mqjrOsUX_k9oQtfrluMkGORtBwiPsUyG/view?usp=sharing

Pretraining Parameters

链接：https://pan.baidu.com/s/1HMdu_2w1VcMlizjA3HOjLw 提取码：8f7t

Training Set

2185 https://drive.google.com/file/d/1fcJj4aYdJ6N-TvvxSZ_sBo-xhtd_w-eJ/view?usp=sharing

2985 https://drive.google.com/file/d/1mYjaT_FTlY4atd-c0WdQ-0beZIpf8fgh/view?usp=sharing

Testing Set

链接：https://pan.baidu.com/s/1fN-AsBiKTbMRsye0Lr8K7g 提取码：l2u9

google https://drive.google.com/file/d/1dQWrhO-LHVACDKCTrvdc6eIbcyH7Yzp_/view?usp=sharing

Result Saliency Maps

链接：https://pan.baidu.com/s/1yNzEhwQkTRjTFE9VMH1OTg 提取码：npg7

google https://drive.google.com/file/d/1Ne4Xx63bHbt2IjpFE4fe2NX917cf9qzQ/view?usp=sharing

Evaluation Code

链接：https://pan.baidu.com/s/1EtKTNVPQAW_iLm8pA1POmQ 提取码：86gt

https://drive.google.com/file/d/1-fXbORnXNVfvm7uarXLX6w9PuVhs-25d/view?usp=sharing

Citation

If you find the information useful, please consider citing:

@inproceedings{liu2021tritransnet,
  title={TriTransNet: RGB-D Salient Object Detection with a Triplet Transformer Embedding Network},
  author={Liu, Zhengyi and Wang, Yuan and Tu, Zhengzheng and Xiao, Yun and Tang, Bin},
  booktitle={Proceedings of the 29th ACM International Conference on Multimedia},
  pages={4481--4490},
  year={2021}
}

If you have some questions, please contact: liuzywen@ahu.edu.cn