Abstract. We address the problem of novel view synthesis: given an input image, synthesizing new images of the same object or scene observed from arbitrary viewpoints. We approach this as a learning task but, critically, instead of learning to synthesize pixels from scratch, we learn to copy them from the input image. Our approach exploits the observation that the visual appearance of different views of the same instance is highly correlated, and such correlation could be explicitly learned by training a convolutional neural network (CNN) to predict appearance flows -2-D coordinate vectors specifying which pixels in the input view could be used to reconstruct the target view. Furthermore, the proposed framework easily generalizes to multiple input views by learning how to optimally combine single-view predictions. We show that for both objects and scenes, our approach is able to synthesize novel views of higher perceptual quality than previous CNN-based techniques. Fig. 1. Given an input image, our goal is to synthesize novel views of the same object (left) or scene (right) corresponding to various camera transformations (Ti). Our approach, based on learning appearance flows, is able to generate higher-quality results than the previous method that directly outputs pixels in the target view [1].

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The hallmark reaction of P450 monooxygenase involves activation of C–H bond and the production of a hydroxyl. P450s tailoring natural product could further oxidize the hydroxyl to carboxylic acid. However, heterogeneously expressed plant P450s display poor chemo- and regioselectivity in microbes, restricting the efficient biosynthesis of related natural products. CYP72A63 is a P450 enzyme previously used for the biosynthesis of glycyrrhetinic acid, and its poor selectivity resulted in oxidation of 11-oxo-β-amyrin to a mixture of rare licorice triterpenoids (glycyrrhetol, glycyrrhetaldehyde, glycyrrhetinic acid, and 29-OH-11-oxo-β-amyrin). In this study, we have identified key residues, which influence the enzyme–substrate hydrophobic interaction, in controlling the chemo- and regioselectivity of the enzyme and engineered the enzyme toward selectivity oxidation to hydroxyl and carboxylic acid. Moreover, tuning the redox partner of the P450 leads to selective production of glycyrrhetaldehyde, a good starting point for further modification. In this study, controlling the catalytic property of plant P450s prove to be of great use in the synthesis of desired licorice triterpenoids, which can be used in biosynthesis of other terpenoid natural products.

1 SG, 9.2%, 180 fps 3 SGs, 6.0% , 76 fps 5 SGs, 3.4 %, 55 fps 7 SGs, 2.0% , 36 fps 9 SGs, 1.1% , 27 fps 1 ASG 11 SGs, 0.54% , 22 fps 13 SGs, 0.26% , 19 fps 15 SGs, 0.11% , 17 fps 1 ASG, 0.10% , 125 fps reference Figure 1: Comparison of the SG (Spherical Gaussian) based approximation with the ASG (Anisotropic Spherical Gaussian) based approximation in rendering a highly anisotropic metal dish, under an environment light and two local lights. The BRDF of the metal dish is approximated by different number of ASGs or SGs in different images. Notice the superior property of ASGs over SGs. The result generated by 1 ASG already matches the path-traced reference well (with a L 2 error of 0.10%), and achieves a high framerate of 125 fps, while, to achieve a similar quality, more than 10 SGs are required, but with much lower framerates (19 fps for 13 SGs or 17 fps for 15 SGs). The L 2 error and the framerates for each configuration are also given in the corresponding subtitle. AbstractWe present a novel anisotropic Spherical Gaussian (ASG) function, built upon the Bingham distribution [Bingham 1974], which is much more effective and efficient in representing anisotropic spherical functions than Spherical Gaussians (SGs). In addition to retaining many desired properties of SGs, ASGs are also rotationally invariant and capable of representing all-frequency signals. To further strengthen the properties of ASGs, we have derived approximate closed-form solutions for their integral, product and convolution operators, whose errors are nearly negligible, as validated by quantitative analysis. Supported by all these operators, ASGs can be adapted in existing SG-based applications to enhance their scalability in handling anisotropic effects. To demonstrate the accuracy and efficiency of ASGs in practice, we have applied ASGs in two important SG-based rendering applications and the experimental results clearly reveal the merits of ASGs.