natural-adv-examples
A Harder ImageNet Test Set (CVPR 2021) (by hendrycks)
LBGAT
Learnable Boundary Guided Adversarial Training (ICCV2021) (by dvlab-research)
| natural-adv-examples | LBGAT | |
|---|---|---|
| 1 | 2 | |
| 572 | 33 | |
| - | - | |
| 0.0 | 2.8 | |
| about 2 months ago | 11 months ago | |
| Python | Python | |
| MIT License | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
natural-adv-examples
Posts with mentions or reviews of natural-adv-examples.
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We haven't tracked posts mentioning natural-adv-examples yet.
Tracking mentions began in Dec 2020.
LBGAT
Posts with mentions or reviews of LBGAT.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-06-13.
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[D] Yet another case of plagiarism in ICCV. The ICCV 2021 paper "Learnable Boundary Guided Adversarial Training"(arxiv 2011.11164) with the BMVC 2020 paper "Adversarial Concurrent Training: Optimizing Robustness and Accuracy Trade-off of Deep Neural Networks" (arxiv 2008.07015)
Hi everyone, I am the first author of ICCV 2021 paper A (Learnable Boundary Guided Adversarial Training), Jiequan Cui. I give the following facts to prove that our paper A completely stems from our own ideas without referring to BMVC 2020 paper B (Adversarial Concurrent Training: Optimizing Robustness and Accuracy Trade-off of Deep Neural Networks). 1. Our paper was first submitted to CVPR 2020 and got rejected. The submission date was Nov. 15, 2019 (screenshot: https://github.com/dvlab-research/LBGAT/blob/main/assets/record_of_our_submittion_to_cvpr2020.png). Our CVPR 2020 overleaf project screenshot is in https://github.com/dvlab-research/LBGAT/blob/main/assets/overleaf_history.png. Our idea and framework were already there (full pdf submission: https://github.com/dvlab-research/LBGAT/blob/main/assets/manuscripts_submitted_to_cvpr2020.pdf). Since it was rejected, we resubmitted it to CVPR 2021 (rejected), and ICCV 2021 with more results. In comparison, paper B is accepted in BMVC 2020 with submission deadline April 30, 2020, later than our first submission date Nov. 15, 2019. Authors of B submitted the paper to arXiv on August 16, 2020. 2. our paper is with released code 11 months ago while paper B released code 10 months ago. Our code: https://github.com/dvlab-research/LBGAT Paper B code: https://github.com/NeurAI-Lab/ACT
What are some alternatives?
When comparing natural-adv-examples and LBGAT you can also consider the following projects:
transferlearning - Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
ACT - The official PyTorch code for BMVC'20 Paper "Adversarial Concurrent Training: Optimizing Robustness and Accuracy Trade-off of Deep Neural Networks"
ModelNet40-C - Repo for "Benchmarking Robustness of 3D Point Cloud Recognition against Common Corruptions" https://arxiv.org/abs/2201.12296