Unveiling the Power of Mixup for Stronger Classifiers

Mixup-based data augmentations have achieved great success as regularizers for deep neural networks. However, existing methods rely on deliberately handcrafted mixup policies, which ignore or oversell the semantic matching between mixed samples and labels. Driven by their prior assumptions, early methods attempt to smooth decision boundaries by random linear interpolation while others focus on maximizing class-related information via offline saliency optimization. As a result, the issue of label mismatch has not been well addressed. Additionally, the optimization stability of mixup training is constantly troubled by the label mismatch. To address these challenges, we first reformulate mixup for supervised classification as two sub-tasks, mixup sample generation and classification, then propose Automatic Mixup (AutoMix), a revolutionary mixup framework. Specifically, a learnable lightweight Mix Block (MB) with a cross-attention mechanism is proposed to generate a mixed sample by modeling a fair relationship between the pair of samples under direct supervision of the corresponding mixed label. Moreover, the proposed Momentum Pipeline (MP) enhances training stability and accelerates convergence on top of making the Mix Block fully trained end-to-end. Extensive experiments on five popular classification benchmarks show that the proposed approach consistently outperforms leading methods by a large margin.Comment: The second version of AutoMix. 12 pages, 7 figure

SCARB2/LIMP-2 Regulates IFN Production of Plasmacytoid Dendritic Cells by Mediating Endosomal Translocation of TLR9 and Nuclear Translocation of IRF7

Scavenger receptor class B, member 2 (SCARB2) is essential for endosome biogenesis and reorganization and serves as a receptor for both β-glucocerebrosidase and enterovirus 71. However, little is known about its function in innate immune cells. In this study, we show that, among human peripheral blood cells, SCARB2 is most highly expressed in plasmacytoid dendritic cells (pDCs), and its expression is further upregulated by CpG oligodeoxynucleotide stimulation. Knockdown of SCARB2 in pDC cell line GEN2.2 dramatically reduces CpG-induced type I IFN production. Detailed studies reveal that SCARB2 localizes in late endosome/lysosome of pDCs, and knockdown of SCARB2 does not affect CpG oligodeoxynucleotide uptake but results in the retention of TLR9 in the endoplasmic reticulum and an impaired nuclear translocation of IFN regulatory factor 7. The IFN-I production by TLR7 ligand stimulation is also impaired by SCARB2 knockdown. However, SCARB2 is not essential for influenza virus or HSV-induced IFN-I production. These findings suggest that SCARB2 regulates TLR9-dependent IFN-I production of pDCs by mediating endosomal translocation of TLR9 and nuclear translocation of IFN regulatory factor 7.Chinese Academy of Sciences (Grant KJZD-EW-L10-02)Beijing Municipal Commission of Science and Technology (Grant SCW 2014-09

SCARB2/LIMP-2 Regulates IFN Production of Plasmacytoid Dendritic Cells by Mediating Endosomal Translocation of TLR9 and Nuclear Translocation of IRF7

Scavenger receptor class B, member 2 (SCARB2) is essential for endosome biogenesis and reorganization and serves as a receptor for both β-glucocerebrosidase and enterovirus 71. However, little is known about its function in innate immune cells. In this study, we show that, among human peripheral blood cells, SCARB2 is most highly expressed in plasmacytoid dendritic cells (pDCs), and its expression is further upregulated by CpG oligodeoxynucleotide stimulation. Knockdown of SCARB2 in pDC cell line GEN2.2 dramatically reduces CpG-induced type I IFN production. Detailed studies reveal that SCARB2 localizes in late endosome/lysosome of pDCs, and knockdown of SCARB2 does not affect CpG oligodeoxynucleotide uptake but results in the retention of TLR9 in the endoplasmic reticulum and an impaired nuclear translocation of IFN regulatory factor 7. The IFN-I production by TLR7 ligand stimulation is also impaired by SCARB2 knockdown. However, SCARB2 is not essential for influenza virus or HSV-induced IFN-I production. These findings suggest that SCARB2 regulates TLR9-dependent IFN-I production of pDCs by mediating endosomal translocation of TLR9 and nuclear translocation of IFN regulatory factor 7

Dominant and Complementary Emotion Recognition from Still Images of Faces

Emotion recognition has a key role in affective computing. Recently, fine-grained emotion analysis, such as compound facial expression of emotions, has attracted high interest of researchers working on affective computing. A compound facial emotion includes dominant and complementary emotions (e.g., happily-disgusted and sadly-fearful), which is more detailed than the seven classical facial emotions (e.g., happy, disgust, and so on). Current studies on compound emotions are limited to use data sets with limited number of categories and unbalanced data distributions, with labels obtained automatically by machine learning-based algorithms which could lead to inaccuracies. To address these problems, we released the iCV-MEFED data set, which includes 50 classes of compound emotions and labels assessed by psychologists. The task is challenging due to high similarities of compound facial emotions from different categories. In addition, we have organized a challenge based on the proposed iCV-MEFED data set, held at FG workshop 2017. In this paper, we analyze the top three winner methods and perform further detailed experiments on the proposed data set. Experiments indicate that pairs of compound emotion (e.g., surprisingly-happy vs happily-surprised) are more difficult to be recognized if compared with the seven basic emotions. However, we hope the proposed data set can help to pave the way for further research on compound facial emotion recognition