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advertorch

A Toolbox for Adversarial Robustness Research

it-osr-code

This is the code of the paper "Orthogonal-Coding Based Feature Generation for Transductive Open-Set Recognition via Dual-Space Consistent Sampling", which is submitted to Journal for review and the arXiv version is available on https://arxiv.org/pdf/2207.05957.pdf. The authors are Jiayin Sun and Qiulei Dong.

make_pairs

make pairs for face verification

moep-ae-osr

This is the code for the paper "MoEP-AE: Autoencoding Mixtures of Exponential Power Distributions for Open-Set Recognition", which is under review. The authors are Jiayin Sun, Hong Wang, and Qiulei Dong.

moep-ae-osr-code

This is the code for the paper "MoEP-AE: Autoencoding Mixtures of Exponential Power Distributions for Open-Set Recognition", which is under review. The authors are Jiayin Sun, Hong Wang, and Qiulei Dong. Environments: Python 3.7.7, Pytorch 1.7.1, CUDA 10.1.105, GPU NVIDIA TITAN X To train: python train_MoEP_AE_macro_F1_scores.py To test: python eval_MoEP_AE_macro_F1_scores.py

pbvs2022multi-modal-aerial-view-object-classification-challenge-track2-2nd

stan-osfgr-code

This is the code for our paper: "Spatial-Temporal Attention Network for Open-Set Fine-Grained Image Recognition", which is under review.