ExCon: Explanation-driven Supervised Contrastive Learning

Last update: Nov 01, 2022

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Deep Learning ExCon

Overview

ExCon: Explanation-driven Supervised Contrastive Learning

Contributors of this repo:

Zhibo Zhang ([email protected])
Jongseong Jang ([email protected])
Ruiwen Li ([email protected])

Run ExCon:

python3 ExCon/main_supcon.py --epochs=200 --explainer="GradCAM" --dataset="cifar100" --batch_size=256 --method="Ex_SupCon" --learning_rate=0.5 --temp=0.1 --cosine --negative_pair=1 --validation=1 --background_anchor=0 --exp_epochs=0

If you use our code, please cite our paper:

@misc{zhang2021excon,
      title={ExCon: Explanation-driven Supervised Contrastive Learning for Image Classification},
      author={Zhibo Zhang and Jongseong Jang and Chiheb Trabelsi and Ruiwen Li and Scott Sanner and Yeonjeong Jeong and Dongsub Shim},
      year={2021},
      eprint={2111.14271},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}

Reference Repos:

[1] https://github.com/HobbitLong/SupContrast

Owner

Zhibo (Darren) Zhang

Master in ML @ UToronto | R&D @ Google Brain TensorFlow Team (GSoC '20)

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ExCon: Explanation-driven Supervised Contrastive Learning

Related tags

Overview

ExCon: Explanation-driven Supervised Contrastive Learning

Contributors of this repo:

Run ExCon:

Reference Repos:

Owner

Zhibo (Darren) Zhang

Code repository for Self-supervised Structure-sensitive Learning, CVPR'17

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Character-Input - Create a program that asks the user to enter their name and their age

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A library built upon PyTorch for building embeddings on discrete event sequences using self-supervision

SymmetryNet: Learning to Predict Reflectional and Rotational Symmetries of 3D Shapes from Single-View RGB-D Images

An unofficial personal implementation of UM-Adapt, specifically to tackle joint estimation of panoptic segmentation and depth prediction for autonomous driving datasets.

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