Diffusion360: Seamless 360 Degree Panoramic Image Generation based on Diffusion Models

This is a technical report on the 360-degree panoramic image generation task based on diffusion models. Unlike ordinary 2D images, 360-degree panoramic images capture the entire $360^\circ\times 180^\circ$ field of view. So the rightmost and the leftmost sides of the 360 panoramic image should be continued, which is the main challenge in this field. However, the current diffusion pipeline is not appropriate for generating such a seamless 360-degree panoramic image. To this end, we propose a circular blending strategy on both the denoising and VAE decoding stages to maintain the geometry continuity. Based on this, we present two models for \textbf{Text-to-360-panoramas} and \textbf{Single-Image-to-360-panoramas} tasks. The code has been released as an open-source project at \href{https://github.com/ArcherFMY/SD-T2I-360PanoImage}{https://github.com/ArcherFMY/SD-T2I-360PanoImage} and \href{https://www.modelscope.cn/models/damo/cv_diffusion_text-to-360panorama-image_generation/summary}{ModelScope}Comment: 2 pages, 8 figures, Tech. Repor

A load-balancing mechanism for distributed SDN control plane using response time.

Software-Defined Networking (SDN) has become a popular paradigm for managing large-scale networks including cloud servers and data centers because of its advantages of centralized management and programmability. The issues of scalability and reliability that a single centralized controller suffers makes distributed controller architectures emerge. One key limitation of distributed controllers is the statically configured switch-controller mapping, easily causing uneven load distribution among controllers. Previous works have proposed load-balancing methods with switch migration to address this issue. However, the higher-load controller is always directly considered as the overloaded controller that need to shift its load to other controllers, even if it has no response time delay. The pursuit of absolute load-balancing effect can also result in frequent network delays and service interruptions. Additionally, if there are several overloaded controllers, just one controller with the maximum load can be addressed within a single load-balancing operation, reducing load-balancing efficiency. To address these problems, we propose SMCLBRT, a load-balancing strategy of multiple SDN controllers based on response time, considering the changing features of real-time response times versus controller loads. By selecting the appropriate response time threshold and dealing with multiple overloading controllers simultaneously, it can well solve load-balancing problem in SDN control plane with multiple overloaded controllers. Simulation experiments exhibit the effectiveness of our scheme.N/

A Hierarchical Representation Network for Accurate and Detailed Face Reconstruction from In-The-Wild Images

Limited by the nature of the low-dimensional representational capacity of 3DMM, most of the 3DMM-based face reconstruction (FR) methods fail to recover high-frequency facial details, such as wrinkles, dimples, etc. Some attempt to solve the problem by introducing detail maps or non-linear operations, however, the results are still not vivid. To this end, we in this paper present a novel hierarchical representation network (HRN) to achieve accurate and detailed face reconstruction from a single image. Specifically, we implement the geometry disentanglement and introduce the hierarchical representation to fulfill detailed face modeling. Meanwhile, 3D priors of facial details are incorporated to enhance the accuracy and authenticity of the reconstruction results. We also propose a de-retouching module to achieve better decoupling of the geometry and appearance. It is noteworthy that our framework can be extended to a multi-view fashion by considering detail consistency of different views. Extensive experiments on two single-view and two multi-view FR benchmarks demonstrate that our method outperforms the existing methods in both reconstruction accuracy and visual effects. Finally, we introduce a high-quality 3D face dataset FaceHD-100 to boost the research of high-fidelity face reconstruction. The project homepage is at https://younglbw.github.io/HRN-homepage/.Comment: Accepted by CVPR202

Box-supervised Instance Segmentation with Level Set Evolution

In contrast to the fully supervised methods using pixel-wise mask labels, box-supervised instance segmentation takes advantage of the simple box annotations, which has recently attracted a lot of research attentions. In this paper, we propose a novel single-shot box-supervised instance segmentation approach, which integrates the classical level set model with deep neural network delicately. Specifically, our proposed method iteratively learns a series of level sets through a continuous Chan-Vese energy-based function in an end-to-end fashion. A simple mask supervised SOLOv2 model is adapted to predict the instance-aware mask map as the level set for each instance. Both the input image and its deep features are employed as the input data to evolve the level set curves, where a box projection function is employed to obtain the initial boundary. By minimizing the fully differentiable energy function, the level set for each instance is iteratively optimized within its corresponding bounding box annotation. The experimental results on four challenging benchmarks demonstrate the leading performance of our proposed approach to robust instance segmentation in various scenarios. The code is available at: https://github.com/LiWentomng/boxlevelset.Comment: 17 page, 4figures, ECCV202

Medical image registration based on PCA and M_PSNR

Medical image registration is not only the premise of medical image fusion, but also the focus of medical image processing. It plays an important role in clinical diagnosis and treatment planning. Aiming at the problem of mutual information value in image registration, a PCA neural network and M_PSNR based method for rigid registration of reference and floating images was proposed. In this method, the centroid of the image needs to be figured out through the image matrix, and the rotation Angle and translation of the image registration can be calculated by PCA method to obtain the optimal rotation transformation and the initial registration value. Finally, M_PSNR method improved by PSNR was used for similarity test to increase the speed and efficiency of registration and simplify the calculation process

Hepatitis B virus–induced imbalance of inflammatory and antiviral signaling by differential phosphorylation of STAT1 in human monocytes

It is not clear how hepatitis B virus (HBV) modulates host immunity during chronic infection. In addition to the key mediators of inflammatory response in viral infection, monocytes also express a high-level IFN-stimulated gene, CH25H, upon response to IFN-a exerting an antiviral effect. In this study, the mechanism by which HBV manipulates IFN signaling in human monocytes was investigated. We observed that monocytes from chronic hepatitis B patients express lower levels of IFN signaling/stimulated genes and higher levels of inflammatory cytokines compared with healthy donors. HBV induces monocyte production of inflammatory cytokines via TLR2/MyD88/NF-kB signaling and STAT1-Ser727 phosphorylation and inhibits IFN-a–induced stat1, stat2, and ch25h expression through the inhibition of STAT1-Tyr701 phosphorylation and in an IL-10–dependent, partially autocrine manner. Further, we found that enhancement of STAT1 activity with a small molecule (2-NP) rescued HBV-mediated inhibition of IFN signaling and counteracted the induction of inflammatory cytokines. In conclusion, HBV contributes to the monocyte inflammatory response but inhibits their IFN-a/b responsiveness to impair antiviral innate immunity. These effects are mediated via differential phosphorylation of Tyr701 and Ser727 of STAT1

Mindfulness-based stress reduction combined with early cardiac rehabilitation improves negative mood states and cardiac function in patients with acute myocardial infarction assisted with an intra-aortic balloon pump: a randomized controlled trial

ObjectiveTo investigate the clinical effects of mindfulness-based stress reduction (MBSR) intervention combined with early cardiac rehabilitation (CR) on patients with acute myocardial infarction (AMI) assisted with an intra-aortic balloon pump (IABP).MethodsA total of 100 AMI patients with IABP assistance due to hemodynamic instability at Wuhan Asia Heart Hospital were enrolled in the study. The participants were divided into two groups using the random number table method (n = 50 each group). Patients receiving routine CR were assigned to the CR control group, while patients receiving MBSR plus CR were assigned to the MBSR intervention group. The intervention was performed twice a day until the removal of the IABP (5–7 days). Each patient's level of anxiety/depression and negative mood state were evaluated before and after intervention using the self-rating anxiety scale (SAS), self-rating depression scale (SDS), and profiles of mood state scale (POMS). The results of the control and intervention groups were compared. IABP-related complications and left ventricular ejection fraction (LVEF), measured with echocardiography, were also assessed and compared between the two groups.ResultsThe SAS, SDS, and POMS scores were lower in the MBSR intervention group than in the CR control group (P < 0.05). There were also less IABP-related complications in the MBSR intervention group. LVEF was significantly improved in both groups, but the degree of LVEF improvement was more significant in the MBSR intervention group than in the CR control group (P < 0.05).ConclusionsMBSR combined with early CR intervention can assist in alleviating anxiety, depression, and other negative mood states, reduce IABP-related complications, and further improve cardiac function in AMI patients with IABP assistance

Can integration reduce inequity in healthcare utilization?: evidence and hurdles in China

Background: Integration of medical insurance schemes has been prioritized as one of the key strategies to address inequity in China's health system. The first pilot attempt to integrate started in 2003 and later expanded nationwide. This study aims to assess its intended impact on inequity in inpatient service utilization and identify the main determinants contributing to ieffectiveness. Methods: A total of 49,365 respondents in the pilot integrated area and 77,165 respondents in the non-integration area were extracted from the Fifth National Health Services Survey. A comparative analysis was conducted between two types of areas. We calculate a concentration index (CI) and horizontal inequity index (HI) in inpatient service utilization and decompose the two indices. Results: Insurance integration played a positive role in reducing inequality in inpatient service utilization to some extent. A 13.23% lower in HI, a decrease in unmet inpatient care and financial barriers to inpatient care in the pilot integrated area compared with the non-integration area; decomposition analysis showed that the Urban-Rural Residents Basic Medical Insurance, a type of integrated insurance, contributed 37.49% to reducing inequality in inpatient service utilization. However, it still could not offset the strong negative effect of income and other insurance schemes that have increased inequality. Conclusions: The earlier pilot attempt for integrating medical insurance was not enough to counteract the influence of factors which increased the inequality in inpatient service utilization. Further efforts to address the inequality should focus on widening access to financing, upgrading the risk pool, reducing gaps within and between insurance schemes, and providing broader chronic disease benefit packages. Social policies that target the needs of the poor with coordinated efforts from various levels and agencies of the government are urgently needed