GithubHelp home page GithubHelp logo

ImageNet-VID dataset about pymdnet HOT 7 OPEN

hyseob avatar hyseob commented on August 19, 2024
ImageNet-VID dataset

from pymdnet.

Comments (7)

hyseob avatar hyseob commented on August 19, 2024

Hi, @Actmaiji
It is the 2015 version. I will add the link that you mentioned to the readme. Thank you :)

from pymdnet.

Actmaiji avatar Actmaiji commented on August 19, 2024

thanks a lot.But I still have two quetions:first,when you training on vot ot ImageNet-VID,do you have any method to verify the training results(two classification model) or just verify on online tracking? during training ,the precision reach 0.994(Imagenet),but the online tracking results is worse than 0.971.thanks a lot

from pymdnet.

hyseob avatar hyseob commented on August 19, 2024

@Actmaiji I verified the pretraining policy using the last 20% of frames for each video as a separated validation set, and added them to the training set for the final release. The online finetuning is just verified on tracking. Thank you :)

from pymdnet.

Actmaiji avatar Actmaiji commented on August 19, 2024

Thanks a lots for your replying.Sorry,I coundn't understand what the "trainging set" and the "final release" exactly mean.Do you mean that when n_cycle=50. In # Main trainig loop when i = 49,we added the validation set to the training set, and the model parameters still update? And the final release is the final model?Thank you :)

from pymdnet.

hyseob avatar hyseob commented on August 19, 2024

The "training set" means the entire data used for pretraining.
To fine appropriate hyperparameters (learning rate, number of cycles, etc.) for pretraining, I used 80% of Imagenet-VID as a training set and the rest 20% as a validation set.
After finding the hyperparameters, I re-train the model from the scratch using the entire Imagenet-VID as a training set without a separated validation set, which is what the "final release" of the code (pretrain/train_mdnet.py) does.

from pymdnet.

Actmaiji avatar Actmaiji commented on August 19, 2024

Thank you. I got it.Did you use the same training strategy on vot training dataset? I used to verify it on
tracking the data set, just initializing the first frame and then testing the two classification model.Do you think that will work?

from pymdnet.

sieumap43 avatar sieumap43 commented on August 19, 2024

hi,what do you mean the "ImageNet-VID dataset" ? Because I can find the 2015 :http://bvisionweb1.cs.unc.edu/ilsvrc2015/download-videos-3j16.php#vid and the 2017. Can any guy give me a link of the ImageNet-VID dataset ?thanks a lot.

The link just died recently. Does someone have the dataset or an alternative link?

from pymdnet.

Related Issues (20)

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.