Local Manifold Augmentation for Multiview Semantic Consistency

Multiview self-supervised representation learning roots in exploring semantic consistency across data of complex intra-class variation. Such variation is not directly accessible and therefore simulated by data augmentations. However, commonly adopted augmentations are handcrafted and limited to simple geometrical and color changes, which are unable to cover the abundant intra-class variation. In this paper, we propose to extract the underlying data variation from datasets and construct a novel augmentation operator, named local manifold augmentation (LMA). LMA is achieved by training an instance-conditioned generator to fit the distribution on the local manifold of data and sampling multiview data using it. LMA shows the ability to create an infinite number of data views, preserve semantics, and simulate complicated variations in object pose, viewpoint, lighting condition, background etc. Experiments show that with LMA integrated, self-supervised learning methods such as MoCov2 and SimSiam gain consistent improvement on prevalent benchmarks including CIFAR10, CIFAR100, STL10, ImageNet100, and ImageNet. Furthermore, LMA leads to representations that obtain more significant invariance to the viewpoint, object pose, and illumination changes and stronger robustness to various real distribution shifts reflected by ImageNet-V2, ImageNet-R, ImageNet Sketch etc

ILSGAN: Independent Layer Synthesis for Unsupervised Foreground-Background Segmentation

Unsupervised foreground-background segmentation aims at extracting salient objects from cluttered backgrounds, where Generative Adversarial Network (GAN) approaches, especially layered GANs, show great promise. However, without human annotations, they are typically prone to produce foreground and background layers with non-negligible semantic and visual confusion, dubbed "information leakage", resulting in notable degeneration of the generated segmentation mask. To alleviate this issue, we propose a simple-yet-effective explicit layer independence modeling approach, termed Independent Layer Synthesis GAN (ILSGAN), pursuing independent foreground-background layer generation by encouraging their discrepancy. Specifically, it targets minimizing the mutual information between visible and invisible regions of the foreground and background to spur interlayer independence. Through in-depth theoretical and experimental analyses, we justify that explicit layer independence modeling is critical to suppressing information leakage and contributes to impressive segmentation performance gains. Also, our ILSGAN achieves strong state-of-the-art generation quality and segmentation performance on complex real-world data.Comment: Accepted by AAAI 202

Learning Foreground-Background Segmentation from Improved Layered GANs

Deep learning approaches heavily rely on high-quality human supervision which is nonetheless expensive, time-consuming, and error-prone, especially for image segmentation task. In this paper, we propose a method to automatically synthesize paired photo-realistic images and segmentation masks for the use of training a foreground-background segmentation network. In particular, we learn a generative adversarial network that decomposes an image into foreground and background layers, and avoid trivial decompositions by maximizing mutual information between generated images and latent variables. The improved layered GANs can synthesize higher quality datasets from which segmentation networks of higher performance can be learned. Moreover, the segmentation networks are employed to stabilize the training of layered GANs in return, which are further alternately trained with Layered GANs. Experiments on a variety of single-object datasets show that our method achieves competitive generation quality and segmentation performance compared to related methods

Herba Epimedii: Anti-oxidative properties and its medical implications

Herba Epimedii is a Chinese herbal medicine with proven efficacy in treating cardiovascular diseases and osteoporosis, and in improving sexual and neurological functions. This efficacy is found to be related to the potent anti-oxidative ability of Herba Epimedii and its flavonoid components, with icarrin as the main effective constituent, along with polysaccharides and vitamin C. These ingredients have been proven to be effective against oxidative-stress related pathologies (cardiovascular diseases, Alzheimer's disease and inflammation) in animal rodent models and in vitro studies. Their antioxidative properties are found to be related to an inductive effect on endogenous freeradical scavenging enzymes such as catalase and glutathione peroxidase and the inherent electron-donating ability of flavonoids. © 2010 licensee MDPI, Basel, Switzerland.published_or_final_versio

DRU classificationに基づく特発性側弯症の適切な観察間隔の設定 多施設研究

Purpose: To determine the capability of the distal radius and ulna (DRU) classification for predicting the scoliosis progression risk within 1 year in patients with adolescent idiopathic scoliosis (AIS) and to develop simple recommendations for follow-up durations. Methods: Medical records of patients with AIS at two tertiary scoliosis referral centers were retrospectively reviewed for their DRU classification and major curve Cobb angles. Baseline DRU grades and Cobb angles with subsequent 1-year follow-up curve magnitudes were studied for scoliosis progression, which was defined as exacerbation of the Cobb angle by ≥ 6°. The relationship between DRU classification and scoliosis progression risk within 1 year was investigated. Patients were divided into three groups according to the Cobb angle (10°-19°, 20°-29°, ≥ 30°). Results: Of the 205 patients with 283 follow-up visits, scoliosis progression occurred in 86 patients (90 follow-up visits). Radius and ulna grades were significantly related to scoliosis progression (p 80% of patients within 1 year. Curve progression was less likely for grades R9 and U7. Most patients with more mature DRU grades did not experience progression, even with Cobb angles ≥ 30°. Conclusion: With R6, R7, and U5, scoliosis may progress within a short period; therefore, careful follow-up with short intervals within 6 months is necessary. R9 and U7 may allow longer 1-year follow-up intervals due to the lower progression risk.博士（医学）・甲第771号・令和3年3月15日© Springer-Verlag GmbH Germany, part of Springer Nature 2020This is a post-peer-review, pre-copyedit version of an article published in European spine journal. The final authenticated version is available online at: http://dx.doi.org/10.1007/s00586-020-06441-4

Managing inter-agency co-ordination : an analysis of district level administration in Hong Kong

published_or_final_versionPolitics and Public AdministrationMasterMaster of Public Administratio

Bidirectionally Deformable Motion Modulation For Video-based Human Pose Transfer

Video-based human pose transfer is a video-to-video generation task that animates a plain source human image based on a series of target human poses. Considering the difficulties in transferring highly structural patterns on the garments and discontinuous poses, existing methods often generate unsatisfactory results such as distorted textures and flickering artifacts. To address these issues, we propose a novel Deformable Motion Modulation (DMM) that utilizes geometric kernel offset with adaptive weight modulation to simultaneously perform feature alignment and style transfer. Different from normal style modulation used in style transfer, the proposed modulation mechanism adaptively reconstructs smoothed frames from style codes according to the object shape through an irregular receptive field of view. To enhance the spatio-temporal consistency, we leverage bidirectional propagation to extract the hidden motion information from a warped image sequence generated by noisy poses. The proposed feature propagation significantly enhances the motion prediction ability by forward and backward propagation. Both quantitative and qualitative experimental results demonstrate superiority over the state-of-the-arts in terms of image fidelity and visual continuity. The source code is publicly available at github.com/rocketappslab/bdmm.Comment: ICCV 202

APSS-ASJ Best Clinical Research Award: Predictability of Curve Progression in Adolescent Idiopathic Scoliosis Using the Distal Radius and Ulna Classification

Study DesignProspective study.PurposeTo determine the risk of clinically significant curve progression in adolescent idiopathic scoliosis (AIS) based on the initial Cobb angle and to test the utility of the distal radius and ulna (DRU) classification in predicting these outcomes.Overview of LiteratureDetermining the remaining growth potential in AIS patients is necessary for predicting prognosis and initiating treatment. Limiting the maturity Cobb angle to <40° and <50° reduces the risk of adulthood progression and need for surgery, respectively. The risk of curve progression is the greatest with skeletally immature patients and thus warrants close monitoring or early intervention. Many parameters exist for measuring the skeletal maturity status in AIS patients, but the DRU classification has been shown to be superior in predicting peak growth and growth cessation. However, its predictive capabilities for curve progression are unknown.MethodsTotally, 513 AIS patients who presented with Risser 0–3 were followed until either skeletal maturity or the need for surgery, with a minimum 2-year follow-up period. Outcomes of 40° and 50° were used for probability analysis based on the cut-offs of adulthood progression risk and surgical threshold, respectively.ResultsAt the R6/U5 grade, most curves (probability of ≥48.1%–55.5%) beyond a Cobb angle of 25° progressed to the 40° threshold. For curves of ≥35°, there was a high risk of unfavorable outcomes, regardless of skeletal maturity. Most patients with the R9 grade did not progress, regardless of the initial curve magnitude (probability of 0% to reach the 50° threshold for an initial Cobb angle of ≥35°).ConclusionsThis large-scale study illustrates the utility of the DRU classification for predicting curve progression and how it may effectively guide the timing of surgery. Bracing may be indicated for skeletally immature patients at an initial Cobb angle of 25°, and those with a scoliosis ≥35° are at an increased risk of an unfavorable outcome, despite being near skeletal maturity