Results 21 to 30 of about 169,247 (258)
NeuTex: Neural Texture Mapping for Volumetric Neural Rendering [PDF]
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021 Recent work has demonstrated that volumetric scene representations combined with differentiable volume rendering can enable photo-realistic rendering for challenging scenes that mesh reconstruction fails on. However, these methods entangle geometry and appearance in a "black-box" volume that cannot be edited.
Xiang, Fanbo +5 more
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Stochasticity from function -- why the Bayesian brain may need no noise [PDF]
, 2019 An increasing body of evidence suggests that the trial-to-trial variability of spiking activity in the brain is not mere noise, but rather the reflection of a sampling-based encoding scheme for probabilistic computing.
Baumbach, Andreas +8 more
core +2 more sources
, 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 ...
Dupont, Emilien +6 more
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MonoNHR: Monocular Neural Human Renderer
2022 International Conference on 3D Vision (3DV), 2022 Existing neural human rendering methods struggle with a single image input due to the lack of information in invisible areas and the depth ambiguity of pixels in visible areas. In this regard, we propose Monocular Neural Human Renderer (MonoNHR), a novel approach that renders robust free-viewpoint images of an arbitrary human given only a single image.
Choi, Hongsuk +5 more
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Invertible Neural BRDF for Object Inverse Rendering [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020 We introduce a novel neural network-based BRDF model and a Bayesian framework for object inverse rendering, i.e., joint estimation of reflectance and natural illumination from a single image of an object of known geometry. The BRDF is expressed with an invertible neural network, namely, normalizing flow, which provides the expressive power of a high ...
Zhe Chen, Shohei Nobuhara, Ko Nishino
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Pulsar: Efficient Sphere-based Neural Rendering [PDF]
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021 We propose Pulsar, an efficient sphere-based differentiable renderer that is orders of magnitude faster than competing techniques, modular, and easy-to-use due to its tight integration with PyTorch. Differentiable rendering is the foundation for modern neural rendering approaches, since it enables end-to-end training of 3D scene representations from ...
Lassner, Christoph, Zollhöfer, Michael
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Generalizable Patch-Based Neural Rendering
, 2022 Neural rendering has received tremendous attention since the advent of Neural Radiance Fields (NeRF), and has pushed the state-of-the-art on novel-view synthesis considerably. The recent focus has been on models that overfit to a single scene, and the few attempts to learn models that can synthesize novel views of unseen scenes mostly consist of ...
Suhail, Mohammed +3 more
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Reconstructing Continuous Light Field From Single Coded Image
IEEE Access, 2023 We propose a method for reconstructing a continuous light field of a target scene from a single observed image. Our method takes the best of two worlds: joint aperture-exposure coding for compressive light-field acquisition, and a neural radiance field ...
Yuya Ishikawa +3 more
doaj +1 more source
Robust 3D Human Reconstruction System From Sparse Views in Outdoor Environments
IEEE AccessWe propose a novel 3D human reconstruction system designed for diverse settings including outdoor environments. Existing methods face the challenges of portability, robustness, and adaptability to environmental variations, as they often rely on sensor ...
Hansoo Park +3 more
doaj +1 more source
Collaborative Neural Rendering Using Anime Character Sheets
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023 Drawing images of characters with desired poses is an essential but laborious task in anime production. Assisting artists to create is a research hotspot in recent years. In this paper, we present the Collaborative Neural Rendering (CoNR) method, which creates new images for specified poses from a few reference images (AKA Character Sheets). In general,
Lin, Zuzeng, Huang, Ailin, Huang, Zhewei
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