MVF-Net: Multi-View 3D Face Morphable Model Regression

We address the problem of recovering the 3D geometry of a human face from a set of facial images in multiple views. While recent studies have shown impressive progress in 3D Morphable Model (3DMM) based facial reconstruction, the settings are mostly restricted to a single view. There is an inherent drawback in the single-view setting: the lack of reliable 3D constraints can cause unresolvable ambiguities. We in this paper explore 3DMM-based shape recovery in a different setting, where a set of multi-view facial images are given as input. A novel approach is proposed to regress 3DMM parameters from multi-view inputs with an end-to-end trainable Convolutional Neural Network (CNN). Multiview geometric constraints are incorporated into the network by establishing dense correspondences between different views leveraging a novel self-supervised view alignment loss. The main ingredient of the view alignment loss is a differentiable dense optical flow estimator that can backpropagate the alignment errors between an input view and a synthetic rendering from another input view, which is projected to the target view through the 3D shape to be inferred. Through minimizing the view alignment loss, better 3D shapes can be recovered such that the synthetic projections from one view to another can better align with the observed image. Extensive experiments demonstrate the superiority of the proposed method over other 3DMM methods.Comment: 2019 Conference on Computer Vision and Pattern Recognitio

CycleACR: Cycle Modeling of Actor-Context Relations for Video Action Detection

The relation modeling between actors and scene context advances video action detection where the correlation of multiple actors makes their action recognition challenging. Existing studies model each actor and scene relation to improve action recognition. However, the scene variations and background interference limit the effectiveness of this relation modeling. In this paper, we propose to select actor-related scene context, rather than directly leverage raw video scenario, to improve relation modeling. We develop a Cycle Actor-Context Relation network (CycleACR) where there is a symmetric graph that models the actor and context relations in a bidirectional form. Our CycleACR consists of the Actor-to-Context Reorganization (A2C-R) that collects actor features for context feature reorganizations, and the Context-to-Actor Enhancement (C2A-E) that dynamically utilizes reorganized context features for actor feature enhancement. Compared to existing designs that focus on C2A-E, our CycleACR introduces A2C-R for a more effective relation modeling. This modeling advances our CycleACR to achieve state-of-the-art performance on two popular action detection datasets (i.e., AVA and UCF101-24). We also provide ablation studies and visualizations as well to show how our cycle actor-context relation modeling improves video action detection. Code is available at https://github.com/MCG-NJU/CycleACR.Comment: technical repor

Self-supervised Learning of Detailed 3D Face Reconstruction

In this paper, we present an end-to-end learning framework for detailed 3D face reconstruction from a single image. Our approach uses a 3DMM-based coarse model and a displacement map in UV-space to represent a 3D face. Unlike previous work addressing the problem, our learning framework does not require supervision of surrogate ground-truth 3D models computed with traditional approaches. Instead, we utilize the input image itself as supervision during learning. In the first stage, we combine a photometric loss and a facial perceptual loss between the input face and the rendered face, to regress a 3DMM-based coarse model. In the second stage, both the input image and the regressed texture of the coarse model are unwrapped into UV-space, and then sent through an image-toimage translation network to predict a displacement map in UVspace. The displacement map and the coarse model are used to render a final detailed face, which again can be compared with the original input image to serve as a photometric loss for the second stage. The advantage of learning displacement map in UV-space is that face alignment can be explicitly done during the unwrapping, thus facial details are easier to learn from large amount of data. Extensive experiments demonstrate the superiority of the proposed method over previous work.Comment: Accepted by IEEE Transactions on Image Processing (TIP

A Completed Multiple Threshold Encoding Pattern for Texture Classification

The binary pattern family has drawn wide attention for texture representation due to its promising performance and simple operation. However, most binary pattern methods focus on local neighborhoods but ignore center pixels. Even if some studies introduce the center based sub-pattern to provide complementary information, existing center based sub-patterns are much weaker than other local neighborhood based sub-patterns. This severe unbalance limits the classification performance of fusion features significantly. To alleviate this problem, this paper designs a multiple threshold center pattern (MTCP) to provide a more discriminative and complementary local texture representation with a compact form. First, a multiple threshold encoding strategy is designed to encode the center pixel that generates three 1-bit binary patterns. Second, it adopts a compact multi-pattern encoding strategy to combine them into a 3-bit MTCP. Furthermore, this paper proposes a completed multiple threshold encoding pattern by fusing the MTCP, local sign pattern, and local magnitude pattern. Comprehensive experimental evaluations on three popular texture classification benchmarks confirm that the completed multiple threshold encoding pattern achieves superior texture classification performance

Effects of Condylar Elastic Properties to Temporomandibular Joint Stress

Mandibular condyle plays an important role in the growth and reconstruction of the temporomandibular joint (TMJ). We aimed to obtain orthotropic elastic parameters of the condyle using a continuous-wave ultrasonic technique and to observe the effects of condylar elastic parameters on stress distribution of the TMJ using finite element analysis (FEA). Using the ultrasonic technique, all nine elastic parameters were obtained, which showed that the mandibular condyle was orthotropic. With the condyle defined as orthotropic, the occlusal stress was transferred fluently and uniformly from the mandible to the TMJ. The stress distribution in the isotropic model showed stepped variation among different anatomical structures with higher stress values in the cartilage and condyle than in the orthotropic model. We conclude that anisotropy has subtle yet significant effects on stress distribution of the TMJ and could improve the reality of simulations

De novo design of a transmembrane Zn²⁺-transporting four-helix bundle.

The design of functional membrane proteins from first principles represents a grand challenge in chemistry and structural biology. Here, we report the design of a membrane-spanning, four-helical bundle that transports first-row transition metal ions Zn(2+) and Co(2+), but not Ca(2+), across membranes. The conduction path was designed to contain two di-metal binding sites that bind with negative cooperativity. X-ray crystallography and solid-state and solution nuclear magnetic resonance indicate that the overall helical bundle is formed from two tightly interacting pairs of helices, which form individual domains that interact weakly along a more dynamic interface. Vesicle flux experiments show that as Zn(2+) ions diffuse down their concentration gradients, protons are antiported. These experiments illustrate the feasibility of designing membrane proteins with predefined structural and dynamic properties

Discovery of novel inhibitors of Streptococcus pneumoniae based on the virtual screening with the homology-modeled structure of histidine kinase (VicK)

<p>Abstract</p> <p>Background</p> <p>Due to the widespread abusage of antibiotics, antibiotic-resistance in <it>Streptococcus pneumoniae </it>(<it>S. pneumoniae</it>) has been increasing quickly in recent years, and it is obviously urgent to develop new types of antibiotics. Two-component systems (TCSs) are the major signal transduction pathways in bacteria and have emerged as potential targets for antibacterial drugs. Among the 13 pairs of TCSs proteins presenting in <it>S. pneumoniae</it>, VicR/K is the unique one essential for bacterium growth, and block agents to which, if can be found, may be developed as effective antibiotics against <it>S. pneumoniae </it>infection.</p> <p>Results</p> <p>Using a structure-based virtual screening (SBVS) method, 105 compounds were computationally identified as potential inhibitors of the histidine kinase (HK) VicK protein from the compound library SPECS. Six of them were then validated <it>in vitro </it>to be active in inhibiting the growth of <it>S. pneumoniae </it>without obvious cytotoxicity to Vero cell. In mouse sepsis models, these compounds are still able to decrease the mortality of the mice infected by <it>S. pneumoniae </it>and one compound even has significant therapeutic effect.</p> <p>Conclusion</p> <p>To our knowledge, these compounds are the first reported inhibitors of HK with antibacterial activity <it>in vitro </it>and <it>in vivo</it>, and are novel lead structures for developing new drugs to combat pneumococcal infection.</p

Determination of 4 Kinds of β-Agonists Residues in Braised Meat by Ultra Performance Liquid Chromatography-Tandem Mass Spectrometry

An ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS) method was developed for the determination of four β-agonists (terbutaline, clenbuterol, ractopamine, salbutamol) in braised meat. Samples were hydrolyzed by β-glucuronidase and cleaned up by an SLS solid phase extraction column. The separation was performed on a Thermo Hypersil Gold C18 column with a gradient elution of 0.1% formic acid water and acetonitrile as mobile phases, ESI+ was used for multiple response monitoring (MRM) and quantitative analysis by internal standard method. The linear relationship of the four β-agonists was good in the concentration range of 0.5 μg/L to 9.5 μg/L, and the correlation coefficient (r) was greater than 0.9988. The limit of detection (LOD) was 0.1 μg/kg, and the limit of quantitation (LOQ) was 0.3 μg/kg. The recoveries were 87.9%~113.7% and RSDs were 1.48%~9.32% at three spiked levels (1, 5 and 9 μg/kg). In a total of 162 batches of braised meat samples, one sample of braised pig’s trotter was found to contain 1.51 μg/kg of clenbuterol and 3.65 μg/kg of ractopamine. Additionally, another sample of braised lamb was found to contain 11.5 μg/kg of clenbuterol. The method is rapid and accurate, and can be used for qualitative and quantitative determination of four β-agonists (terbutaline, clenbuterol, ractopamine, salbutamol) in braised meat