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Lighting Estimation Via Differentiable Screen-Space Rendering.

IEEE Conference on Virtual Reality and 3D User Interfaces (VR)(2020)CCF A

OPPO US Res Ctr

Cited 4|Views40
Abstract
In this paper, we present a method that estimates the real-world lighting condition from a single RGB image of an indoor scene, with information of support plane provided by commercial Augmented Reality (AR) frameworks (e.g., ARCore, ARKit, etc.). First, a Deep Neural Network (DNN) is used to segment the foreground. We only focus on the foreground objects to reduce computation complexity. Then we introduce Differentiable Screen-Space Rendering (DSSR), a novel approach for estimating the normal and lighting condition jointly. We recover the most plausible lighting condition using spherical harmonics. Our approach provides plausible results and considerably enhances the visual realism in AR applications.
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Computing Methodologies,Computer Graphics,Graphics systems and interfaces,Computing Methodologies,Artificial Intelligence,Computer Vision
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要点】:该论文发现滤泡调节T细胞(Tfr)能够直接抑制获取核蛋白的生发中心B细胞,防止自身抗体的发育,同时支持高亲和力外源抗原特异性体液反应,揭示了一种新的自身免疫调节机制。

方法】:研究通过将核蛋白靶向至特定抗原的B细胞,观察Tfr细胞的积累和其免疫抑制特性,进而分析Tfr对生发中心B细胞的调节作用。

实验】:在实验中,研究者使用小鼠模型,通过靶向核蛋白至抗原特异性B细胞,发现能够迅速积累具有免疫抑制特性的Tfr细胞,这些Tfr细胞对获取核蛋白的生发中心B细胞产生了显著的负调节作用,实验结果支持了Tfr与生发中心B细胞直接相互作用在控制效应B细胞反应中的重要作用。具体的数据集名称在文中未提及。