Comments (6)
As far as I know, the paper of this repository is C3DVQA: LINK.
I don't know if I'm right.
Thank you and hoping for replying.
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During training, I used 2 K80 GPU cards for 300 epochs in 38 hours, and the other parameters in opt.py
are reserved not changed.
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@zhixuanli Thanks for your interest on this repo. I will try to address your concerns
During training, I used 2 K80 GPU cards for 300 epochs in 38 hours, and the other parameters in
opt.py
are reserved not changed.
The parameters in opt.py was optimized to train on the VideoSet dataset. If you really want to train the model from scratch, I would recommend to train on CSIQ first and adjust the parameters accordingly.
There is no guarantee the parameters in opt.py
work well on different datasets, especially when the model is trained on different datasets independently.
As far as I know, the paper of this repository is C3DVQA: LINK.
I don't know if I'm right.
Thank you and hoping for replying.
Yes. The link points to the right paper.
Hi, I have trained the C3DVQA model on LIVE-VQA dataset, and the performance is very strange.
I find that in this line:
DVQA/dataset/LIVE/prep_live_score.py
Line 62 in 2172733
the mos should not be subtracted by 100.
Like what's shown in the following table:
change SROCC PLCC
in paper \ 92.61 91.22
origin 100-mos 30.46 29.3
bug fixed mos 31.43 42.2
And the performance is not as well as those in paper C3DVQA.Can you help me? I'm new to this field. Thanks a lot!
Would you give some information that supports your claim ? the mos should not be subtracted by 100..
As far as I know, it is a common practice [1] [2] [3], to linearly rescale MOS such that a larger number indicates better perceptual quality.
The results, i.e. SROCC 0.2930 or 0.4220 are not reasonable. It is not straightforward to get good results when trained on scratch. Even so, the results should be much better, at least 0.87 for most epochs if the model is well trained.
Please read more paper if you want more background knowledge in the VQA field.
[1] Su, Shaolin, Qingsen Yan, Yu Zhu, Cheng Zhang, Xin Ge, Jinqiu Sun, and Yanning Zhang. "Blindly Assess Image Quality in the Wild Guided by a Self-Adaptive Hyper Network." In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 3667-3676. 2020.
[2] Yang, Sheng, Qiuping Jiang, Weisi Lin, and Yongtao Wang. "SGDNet: An End-to-End Saliency-Guided Deep Neural Network for No-Reference Image Quality Assessment." In Proceedings of the 27th ACM International Conference on Multimedia, pp. 1383-1391. 2019.
[3] Kim, Woojae, Jongyoo Kim, Sewoong Ahn, Jinwoo Kim, and Sanghoon Lee. "Deep video quality assessor: From spatio-temporal visual sensitivity to a convolutional neural aggregation network." In Proceedings of the European Conference on Computer Vision (ECCV), pp. 219-234. 2018.
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Really thank you for replying, and it's very helpful!
Actually, I'm not very sure about the mos should not be subtracted by 100
, and I think your advice is right.
In the next, I'll train on CSIQ first and then adjust on LIVE-VQA.
Could you please provide the training hyperparameter (learning rate and so on) for CSIQ and LIVE-VQA?
Thank you!
:)
from dvqa.
Really thank you for replying, and it's very helpful!
Actually, I'm not very sure about
the mos should not be subtracted by 100
, and I think your advice is right.In the next, I'll train on CSIQ first and then adjust on LIVE-VQA.
Could you please provide the training hyperparameter (learning rate and so on) for CSIQ and LIVE-VQA?
Thank you!
:)
Unfortunately I have left tencent for months. I don't have any extra data besides this repo.
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Haha that's so sad.
I'll try to contact the first author by email.
Thank you again for your patiently answering.
I have mailed you with my we-chat id.
If possible, hoping for further communication. :)
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Related Issues (20)
- the performance when using some filters (USM) is not good HOT 1
- ”dis" and "ref" in dataset json file HOT 3
- 请问有小白使用DVQA的使用指南吗? HOT 12
- Minimum hardware requirement for the evaluation of 720p/1080p video HOT 5
- 为什么对视频的评分需要的内存如此之大! HOT 4
- RuntimeError: The size of tensor a (109) must match the size of tensor b (71) at non-singleton dimension 2 HOT 3
- 有预训练好的模型吗,想看看效果
- The question of the training setting of C3DVQA HOT 10
- dataset中json里的mos值是怎么获取?
- How to output the number of FLOPs of this model?
- 请问您有csiq数据集的下载地址吗,找了好久,都没找到。可以给个网盘地址或者发送到邮箱[email protected]。非常感谢。 HOT 5
- How is the MOS label in the dataset videoset mapped? This paper only uses video in yuv format, if only mp4 format is used, is there any performance impact? HOT 2
- Could you provide the download link of video quality datasets? HOT 2
- 训练一个自己的DVQA模型,理想的样本数量是多少? HOT 2
- a question about our eval results HOT 2
- The file(.json) about the dataset information of the LIVE and CSIQ HOT 2
- any pretrained models? HOT 1
- could you introduce some about the dataset size, training environments, training speed HOT 2
- How to use it by CPU? HOT 1
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