Adaptive Multi-NeRF: Exploit Efficient Parallelism in Adaptive Multiple Scale Neural Radiance Field Rendering
T Wang, S Kurabayashi - arXiv preprint arXiv:2310.01881, 2023 - arxiv.org
Recent advances in Neural Radiance Fields (NeRF) have demonstrated significant potential
for representing 3D scene appearances as implicit neural networks, enabling the synthesis …
for representing 3D scene appearances as implicit neural networks, enabling the synthesis …
Palettenerf: Palette-based appearance editing of neural radiance fields
Recent advances in neural radiance fields have enabled the high-fidelity 3D reconstruction
of complex scenes for novel view synthesis. However, it remains underexplored how the …
of complex scenes for novel view synthesis. However, it remains underexplored how the …
Editablenerf: Editing topologically varying neural radiance fields by key points
Neural radiance fields (NeRF) achieve highly photo-realistic novel-view synthesis, but it's a
challenging problem to edit the scenes modeled by NeRF-based methods, especially for …
challenging problem to edit the scenes modeled by NeRF-based methods, especially for …
Rtmv: A ray-traced multi-view synthetic dataset for novel view synthesis
We present a large-scale synthetic dataset for novel view synthesis consisting of~ 300k
images rendered from nearly 2000 complex scenes using high-quality ray tracing at high …
images rendered from nearly 2000 complex scenes using high-quality ray tracing at high …
Nerfdiff: Single-image view synthesis with nerf-guided distillation from 3d-aware diffusion
Novel view synthesis from a single image requires inferring occluded regions of objects and
scenes whilst simultaneously maintaining semantic and physical consistency with the input …
scenes whilst simultaneously maintaining semantic and physical consistency with the input …
Efficient Neural Light Fields (ENeLF) for Mobile Devices
A Peng - arXiv preprint arXiv:2406.00598, 2024 - arxiv.org
Novel view synthesis (NVS) is a challenge in computer vision and graphics, focusing on
generating realistic images of a scene from unobserved camera poses, given a limited set of …
generating realistic images of a scene from unobserved camera poses, given a limited set of …
NeXT: Towards high quality neural radiance fields via multi-skip transformer
Abstract Neural Radiance Fields (NeRF) methods show impressive performance for novel
view synthesis by representing a scene via a neural network. However, most existing NeRF …
view synthesis by representing a scene via a neural network. However, most existing NeRF …
MaskNeRF: Masked Neural Radiance Fields for Sparse View Synthesis
S Hu, L Yu, H Lanqing, T Hu, GH Lee, Z Li - 2022 - openreview.net
Although Neural Radiance Fields (NeRF) has achieved impressive 3D reconstruction with
dense view images, its performance degrades significantly when the training views are …
dense view images, its performance degrades significantly when the training views are …
Transnerf-improving neural radiance fields using transfer learning for efficient scene reconstruction
N Paul - 2021 - essay.utwente.nl
Neural Radiance Fields (NeRF) achieve impressive view synthesis results for a variety of
capture settings including forwardfacing capture of bounded and unbounded scenes. We …
capture settings including forwardfacing capture of bounded and unbounded scenes. We …
Stereo radiance fields (srf): Learning view synthesis for sparse views of novel scenes
Recent neural view synthesis methods have achieved impressive quality and realism,
surpassing classical pipelines which rely on multi-view reconstruction. State-of-the-Art …
surpassing classical pipelines which rely on multi-view reconstruction. State-of-the-Art …