Results 11 to 20 of about 1,597,404 (298)
Predicting specific gravity and viscosity of level-of-detail control in hybrid rendering application. [PDF]
, 2009 This paper presents the hybrid rendering-based Level-of-Detail (LOD) node which aims to simplify the volume visualization workload to improve the interactive rate of the hybrid rendering programming paradigm.
Xu, Zhijie, Holder, Marcus, Xu, Qian
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A Hybrid Rendering Framework for the Real-time Manipulation of Volume and Surface Models [PDF]
, 2009 Stemmed from classical computer graphics research, volume visualization has been steadily growing into an important research field in the last 2 decades. This paper presents a hybrid rendering framework which integrates volume and surface models for real-
Xu, Zhijie, Xu, Qian
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State of the Art on Neural Rendering [PDF]
Computer Graphics Forum, 2020 AbstractEfficient rendering of photo‐realistic virtual worlds is a long standing effort of computer graphics. Modern graphics techniques have succeeded in synthesizing photo‐realistic images from hand‐crafted scene representations. However, the automatic generation of shape, materials, lighting, and other aspects of scenes remains a challenging problem
Ayush Tewari +18 more
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Towards Single 2D Image-Level Self-Supervision for 3D Human Pose and Shape Estimation
Applied Sciences, 2021 Three-dimensional human pose and shape estimation is an important problem in the computer vision community, with numerous applications such as augmented reality, virtual reality, human computer interaction, and so on.
Junuk Cha +7 more
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CoRR, 2020 We propose a framework for learning neural scene representations directly from images, without 3D supervision. Our key insight is that 3D structure can be imposed by ensuring that the learned representation transforms like a real 3D scene. Specifically, we introduce a loss which enforces equivariance of the scene representation with respect to 3D ...
Emilien Dupont +6 more
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SyntheticFur dataset for neural rendering
CoRR, 2021 We introduce a new dataset called SyntheticFur built specifically for machine learning training. The dataset consists of ray traced synthetic fur renders with corresponding rasterized input buffers and simulation data files. We procedurally generated approximately 140,000 images and 15 simulations with Houdini.
Trung Le 0006 +4 more
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IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 Project page with code and videos at https://light-field-neural-rendering.github ...
Mohammed Suhail +3 more
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PERF: Performant, Explicit Radiance Fields
Frontiers in Computer Science, 2022 We present a novel way of approaching image-based 3D reconstruction based on radiance fields. The problem of volumetric reconstruction is formulated as a non-linear least-squares problem and solved explicitly without the use of neural networks.
Sverker Rasmuson +2 more
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BokehMe: When Neural Rendering Meets Classical Rendering
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 We propose BokehMe, a hybrid bokeh rendering framework that marries a neural renderer with a classical physically motivated renderer. Given a single image and a potentially imperfect disparity map, BokehMe generates high-resolution photo-realistic bokeh effects with adjustable blur size, focal plane, and aperture shape.
Juewen Peng +5 more
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Neural Voxel Renderer: Learning an Accurate and Controllable Rendering Tool [PDF]
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020 We present a neural rendering framework that maps a voxelized scene into a high quality image. Highly-textured objects and scene element interactions are realistically rendered by our method, despite having a rough representation as an input. Moreover, our approach allows controllable rendering: geometric and appearance modifications in the input are ...
Konstantinos Rematas, Vittorio Ferrari
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