Dynamic Low-Resolution Distillation for Cost-Efficient End-to-End Text Spotting

End-to-end text spotting has attached great attention recently due to its benefits on global optimization and high maintainability for real applications. However, the input scale has always been a tough trade-off since recognizing a small text instance usually requires enlarging the whole image, which brings high computational costs. In this paper, to address this problem, we propose a novel cost-efficient Dynamic Low-resolution Distillation (DLD) text spotting framework, which aims to infer images in different small but recognizable resolutions and achieve a better balance between accuracy and efficiency. Concretely, we adopt a resolution selector to dynamically decide the input resolutions for different images, which is constraint by both inference accuracy and computational cost. Another sequential knowledge distillation strategy is conducted on the text recognition branch, making the low-res input obtains comparable performance to a high-res image. The proposed method can be optimized end-to-end and adopted in any current text spotting framework to improve the practicability. Extensive experiments on several text spotting benchmarks show that the proposed method vastly improves the usability of low-res models. The code is available at https://github.com/hikopensource/DAVAR-Lab-OCR/.Comment: Accept by ECCV202

MANGO: A Mask Attention Guided One-Stage Scene Text Spotter

Recently end-to-end scene text spotting has become a popular research topic due to its advantages of global optimization and high maintainability in real applications. Most methods attempt to develop various region of interest (RoI) operations to concatenate the detection part and the sequence recognition part into a two-stage text spotting framework. However, in such framework, the recognition part is highly sensitive to the detected results (e.g.), the compactness of text contours). To address this problem, in this paper, we propose a novel Mask AttentioN Guided One-stage text spotting framework named MANGO, in which character sequences can be directly recognized without RoI operation. Concretely, a position-aware mask attention module is developed to generate attention weights on each text instance and its characters. It allows different text instances in an image to be allocated on different feature map channels which are further grouped as a batch of instance features. Finally, a lightweight sequence decoder is applied to generate the character sequences. It is worth noting that MANGO inherently adapts to arbitrary-shaped text spotting and can be trained end-to-end with only coarse position information (e.g.), rectangular bounding box) and text annotations. Experimental results show that the proposed method achieves competitive and even new state-of-the-art performance on both regular and irregular text spotting benchmarks, i.e., ICDAR 2013, ICDAR 2015, Total-Text, and SCUT-CTW1500.Comment: Accepted to AAAI2021. Code is available at https://davar-lab.github.io/publication.html or https://github.com/hikopensource/DAVAR-Lab-OC

The History, Mechanism, and Clinical Application of Auricular Therapy in Traditional Chinese Medicine

Auricular therapy includes acupuncture, electroacupuncture, acupressure, lasering, cauterization, moxibustion, and bloodletting in the auricle. For 2500 years, people have employed auricular therapy for treating diseases, but the methods have been limited to bloodletting and cauterization. Only after 1957, the international scientific community became aware that the map of the ear resembles an inverted fetus, its introduction has led to auricular acupuncture (AA) becoming a more systemic approach, and, following the identification and standardization of more precise points, AA has been employed in clinical applications. The mechanisms of AA are considered to have a close relationship with the autonomic nervous system, the neuroendocrine system, neuroimmunological factors, neuroinflammation, and neural reflex, as well as antioxidation. Auricular therapy has been applied, for example, for pain relief, for the treatment of epilepsy, anxiety, and obesity, and for improving sleep quality. However, the mechanisms and evidence for auricular therapy warrant further study

True 3D imaging with monocular cues using holographic stereography

A quantitative condition is derived to evaluate the monocular accommodation in holographic stereograms. We find that the reconstruction can be viewed as true-3D image when the whole scene is located in the monocular cues area, with compatible monocular cues and binocular cues. In contrast, it reveals incorrect monocular cues in the visible multi-imaging area and the lacking information area. To demonstrate our theoretical predictions, a pupil-function integral imaging algorithm is developed to simulate the mono-eye observation, and a holographic printing system is set up to fabricate the full-parallax holographic stereogram. Both simulation and experimental results match our theoretical predictions.Comment: 16 pages, 4 figure

Down-regulation of PKCζ in renal cell carcinoma and its clinicopathological implications

<p>Abstract</p> <p>Background</p> <p>Metastatic renal cell carcinoma (RCC) is highly resistant to systemic chemotherapy. Unfortunately, nearly all patients die of the metastatic and chemoresistant RCC. Recent studies have shown the atypical PKCζ is an important regulator of tumorigenesis. However, the correlation between PKC<b>ζ </b>expression and the clinical outcome in RCC patients is unclear. We examined the level of PKCζ expression in human RCC.</p> <p>Methods</p> <p>PKCζ mRNA and protein expressions were examined by real-time polymerase chain reaction (PCR) and immunohistochemistry (IHC) respectively in RCC tissues of 144 patients. Cellular cytotoxicity and proliferation were assessed by MTT.</p> <p>Results</p> <p>PKCζ expression was significantly higher in normal than in cancerous tissues (<it>P </it>< 0.0001) by real-time PCR and IHC. Similarly, PKCζ expression was down-regulated in four renal cancer cell lines compared to immortalized benign renal tubular cells. Interestingly, an increase of PKCζ expression was associated with the elevated tumor grade (<it>P </it>= 0.04), but no such association was found in TNM stage (<it>P </it>= 0.13). Tumors with higher PKCζ expression were associated with tumor size (<it>P </it>= 0.048). Expression of higher PKCζ found a poor survival in patients with high tumor grade. Down-regulation of PKCζ showed the significant chemoresistance in RCC cell lines. Inactivation of PKCζ expression enhanced cellular resistance to cisplatin and paclitaxel, and proliferation in HK-2 cells by specific PKC<b>ζ </b>siRNA and inhibitor.</p> <p>Conclusions</p> <p>PKCζ expression was associated with tumorigenesis and chemoresistance in RCC.</p

Oncometabolite 2-Hydroxyglutarate Is a Competitive Inhibitor of α-Ketoglutarate-Dependent Dioxygenases

IDH1 and IDH2 mutations occur frequently in gliomas and acute myeloid leukemia, leading to simultaneous loss and gain of activities in the production of α-ketoglutarate (α-KG) and 2-hydroxyglutarate (2-HG), respectively. Here we demonstrate that 2-HG is a competitive inhibitor of multiple α-KG-dependent dioxygenases, including histone demethylases and the TET family of 5-methlycytosine (5mC) hydroxylases. 2-HG occupies the same space as α-KG does in the active site of histone demethylases. Ectopic expression of tumor-derived IDH1 and IDH2 mutants inhibits histone demethylation and 5mC hydroxylation. In glioma, IDH1 mutations are associated with increased histone methylation and decreased 5-hydroxylmethylcytosine (5hmC). Hence, tumor-derived IDH1 and IDH2 mutations reduce α-KG and accumulate an α-KG antagonist, 2-HG, leading to genome-wide histone and DNA methylation alterations