https://github.com/chenliu-1996/adversarialfocalloss
Adversarial Focal Loss: Asking Your Discriminator for Hard Examples.
Science Score: 10.0%
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Links to: arxiv.org -
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○Scientific vocabulary similarity
Low similarity (6.3%) to scientific vocabulary
Keywords
classification
computer-vision
deep-learning
focal-loss
keypoint-detection
loss-function
machine-learning
Last synced: 6 months ago
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Adversarial Focal Loss: Asking Your Discriminator for Hard Examples.
Basic Info
- Host: GitHub
- Owner: ChenLiu-1996
- Default Branch: main
- Homepage: https://arxiv.org/abs/2207.07739
- Size: 51.5 MB
Statistics
- Stars: 5
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Topics
classification
computer-vision
deep-learning
focal-loss
keypoint-detection
loss-function
machine-learning
Created almost 4 years ago
· Last pushed almost 3 years ago
https://github.com/ChenLiu-1996/AdversarialFocalLoss/blob/main/
# Adversarial Focal Loss:
Asking Your Discriminator for Hard Examples We proposed a generalizable adaptation of Focal Loss to keypoint detection leveraging difficulty scores from a discriminator. Sorry for not being able to provide the code. The team and I conducted this research project while I was working full-time at GE Healthcare, and by the time I organized this repository I had already left the company for PhD. ## Paper Paper can be found [here](https://arxiv.org/pdf/2207.07739.pdf) ## Citation ``` @article{liu2022adversarial, title={Adversarial Focal Loss: Asking Your Discriminator for Hard Examples}, author={Liu, Chen and Dong, Xiaomeng and Potter, Michael and Chang, Hsi-Ming and Soni, Ravi}, journal={arXiv preprint arXiv:2207.07739}, year={2022} } ``` ## Overview and Abstract## Design
## Difficulty Score
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Owner
- Name: Chen Liu
- Login: ChenLiu-1996
- Kind: user
- Location: New Haven
- Company: Yale University
- Website: https://chenliu-1996.github.io/
- Twitter: ChenLiu_1996
- Repositories: 5
- Profile: https://github.com/ChenLiu-1996
CS PhD student at @KrishnaswamyLab, @YaleUniversity. Reviewing Committee member at NeurIPS, ICLR, ICML.
## Design
## Difficulty Score