Results 261 to 270 of about 1,597,404 (298)

E-Sem3DGS: Monocular Human and Scene Reconstruction via Event-Aided Semantic 3DGS. [PDF]

Sensors (Basel)
Yin X, Shi H, Yang K, Zhai J, Guo S, Wang K.   +5 more
europepmc   +1 more source

Image-guided Neural Object Rendering.

, 2020
Justus Thies, Michael Zollhöfer, Christian Theobalt, Marc Stamminger, Matthias Nießner   +4 more
openaire   +2 more sources

BN-NeRF: A fast 3D reconstruction and phenotyping framework for banana plants using handheld devices. [PDF]

Plant Phenomics
Xu X, Chen S, Liu Y, Duan J, Jin M, Fu H, Yang Z.   +6 more
europepmc   +1 more source

Transformer-based 3D pose estimation pipeline with modular SmoothNet integration for animation generation. [PDF]

Sci Rep
Xu X.
europepmc   +1 more source

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Neural scene graph rendering

ACM Transactions on Graphics, 2021
We present a neural scene graph---a modular and controllable representation of scenes with elements that are learned from data. We focus on the forward rendering problem, where the scene graph is provided by the user and references learned elements. The elements correspond to geometry and material definitions of scene objects and constitute the leaves ...
Jan Novak
exaly   +3 more sources

Neural-based Rendering and Application

Proceedings of the 29th ACM International Conference on Multimedia, 2021
Rendering plays an important role in many fields such as virtual reality and film, but the high dependence on computing sources and human experience hinders its application. With the development of deep learning, neural rendering has attracted much attention due to its impressive performance and efficiency than traditional rendering.
openaire   +1 more source

Neural scene representation and rendering

Science, 2018
A scene-internalizing computer program To train a computer to “recognize” elements of a scene supplied by its visual sensors, computer scientists typically use millions of images painstakingly labeled by humans. Eslami et al. developed an artificial vision system, dubbed the Generative Query Network (GQN),
S. M. Ali Eslami, Danilo Jimenez Rezende, Frederic Besse, Fabio Viola, Ari S. Morcos, Marta Garnelo, Avraham Ruderman, Andrei A. Rusu, Ivo Danihelka, Karol Gregor, David P. Reichert, Lars Buesing, Theophane Weber, Oriol Vinyals, Dan Rosenbaum, Neil Rabinowitz, Helen King, Chloe Hillier, Matt Botvinick, Daan Wierstra, Koray Kavukcuoglu, Demis Hassabis   +21 more
openaire   +2 more sources

Neural frame interpolation for rendered content

ACM Transactions on Graphics, 2021
The demand for creating rendered content continues to drastically grow. As it often is extremely computationally expensive and thus costly to render high-quality computer-generated images, there is a high incentive to reduce this computational burden.
Karlis Martins Briedis, Abdelaziz Djelouah, Mark Meyer, Ian McGonigal, Markus Gross 0001, Christopher Schroers   +5 more
openaire   +1 more source

Multi-View Neural Human Rendering

2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020
We present an end-to-end Neural Human Renderer (NHR) for dynamic human captures under the multi-view setting. NHR adopts PointNet++ for feature extraction (FE) to enable robust 3D correspondence matching on low quality, dynamic 3D reconstructions. To render new views, we map 3D features onto the target camera as a 2D feature map and employ an anti ...
Minye Wu, Yuehao Wang, Qiang Hu 0003, Jingyi Yu 0001   +3 more
openaire   +1 more source