Bupt-balancedface
WebApr 1, 2024 · BUPT-Balancedface (BUPT-B) [18] contains 1.3M images from 28K celebrities obtained from MS-Celeb-1M [29]. Divided into 4 demographic groups, it is … WebSep 7, 2024 · BUPT-Balancedface (BUPT) [34], also known as Equal- izedFace in the literature, is the source of our training data. This dataset, in addition to offering subject/class labels for
Bupt-balancedface
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WebJan 28, 2024 · finetune φ 0 by SGD for M = 10 communication rounds on BUPT-Balancedface, with learning rate. 0.001, batch size 512 and weight decay 5 e-4. For reproducibility and fair comparison, all models. Web• Balanced_Softmax.zip: The MxNet models trained with BUPT-Balancedface. The ResNet-34 architecture is used with the guidance of Softmax loss. • CASIA _Softmax.zip: The …
Webface verification. The BUPT-BalancedFace dataset (Wang & Deng,2024) contains an approximately equal number of identities and images of four racial groups1. Balanced Faces in the Wild (Robinson et al.,2024) goes a step further, balancing identities and images across eight categories of race-gender presentation combinations. Also of note is the WebJun 13, 2024 · The models are trained on BUPT-Balancedface with ground truth race/ethnicity and identity labels. The common group fairness criteria like demographic parity distance are improper to evaluate fairness of learnt representations, since they are typically designed to measure independence properties of random variables. However, in …
WebApr 1, 2024 · For RFW and BUPT-Balancedface, the differences between demographic groups are similar but not so large, because the distinction between the demographic groups is only of ethnic origin and not of sex. These differences are important as they mark the percentage of faces successfully matched and faces incorrectly matched for a certain … Webdatasets, called BUPT-Globalface and BUPT-Balancedface dataset, which can be utilized to study racial bias from both data and algorithm aspects. Extensive experiments on …
WebAug 12, 2024 · Further, we provide two skin-tone aware training datasets, called BUPT-Globalface dataset and BUPT-Balancedface dataset, to remove bias in training data. Finally, to mitigate the algorithmic bias, we propose a novel meta-learning algorithm, called Meta Balanced Network (MBN), which learns adaptive margins in large margin loss such …
WebJan 1, 2024 · the full BUPT-BalancedFace dataset and MS1MV3 are sim-ilar, ev en though the MS1MV3 is racially imbalanced. This. is because MS1MV3 is a much larger dataset than BUPT-BalancedFace, and the model ... doge with rice hatWebDec 13, 2024 · ent training databases, namely BUPT-Balancedface (race- balanced), BUPT -Globalface (racial distribution approxi- mately equal to the real distribution of world’ s population), fade away rolling stonesWebBesides, we provide two ethnicity aware training datasets, called BUPT-Globalface and BUPT-Balancedface dataset, which can be utilized to study racial bias from both data and algorithm aspects. Extensive experiments on RFW database show that RL-RBN successfully mitigates racial bias and learns more balanced performance. fade away synonymsWebAll parts listed here are specific to Browning BPS pump-action shotgun unless otherwise noted. MGW offers a large variety of replacement barrels, forearms, stocks, butt plates, … doge with samurai swordWebthe popular BUPT-Balancedface dataset where face images are balanced in various races, and BUPT-Globalface dataset that reveals the real distribution of the world’s population. Similarly, Robinson et al. [21] proposed the BFW benchmark dataset for evaluating the bias of current FR recognition systems. They reduced the performance gaps among ... fadeaway sportsWebBUPT-Balancedface are used for training. From the results, we see several observations: (1) It shows that the White group still outperforms the non-White groups for all the first … doge with ushankaWebSep 7, 2024 · Many existing works have made great strides towards reducing racial bias in face recognition. However, most of these methods attempt to rectify bias that manifests in models during training instead of directly addressing a major source of the bias, the dataset itself. Exceptions to this are BUPT-Balancedface/RFW and Fairface, but these works ... doge with mlg glasses