… , we focus on advanced neural rendering approaches that combine classical rendering with
learnable 3D representations (see Figure 2). The underlying neural 3D representations are …

… for neural rendering. Afterwards, we discuss critical aspects of neural rendering approaches,
… Following, we discuss the landscape of applications that is enabled by neural rendering. …

… pipelines and machine learning components, with a focus on advanced aspects of combining
classical rendering with learnable 3D representations. The literature cited in this review …

… neural network to learn the scene’s neural representations. In this work, we provide a brief
taxonomy of existing popular differentiable rendering … form of neural networks and render this …

… neural rendering is examined using the example of object’s polygonal reconstruction from the
image. The characteristic feature of conducted neural rendering … of neural rendering usage …

… details the latest advances in NERF. … neural renderer to produce output images at the desired
resolution. Research indicates that SteerNeRF markedly enhances the speed of rendering …

… One of the most prominent recent advances in neural rendering is Neural Radiance Fields
(… of the scene that can be rendered from novel viewpoints. The rendered images are of high …

… of modern neural rendering algorithms and present … Neural rendering combines the ideas
from classical computer graphics with the recent advances in deep neural networks to render …

… neural networks can lead to excellent prediction of novel views by learning only from a sparse
set of input images. This neural volume rendering … the density in neural volume rendering, …

… a neural rendering framework comprising an implicit neural 3D scene representation, a neural
renderer, … This approach achieves 10⇥ higher rendering rates than NeRF while providing …