Mixnerf: Modeling a ray with mixture density for novel view synthesis from sparse inputs
Abstract Neural Radiance Field (NeRF) has broken new ground in the novel view synthesis
due to its simple concept and state-of-the-art quality. However, it suffers from severe …
due to its simple concept and state-of-the-art quality. However, it suffers from severe …
Flipnerf: Flipped reflection rays for few-shot novel view synthesis
Abstract Neural Radiance Field (NeRF) has been a mainstream in novel view synthesis with
its remarkable quality of rendered images and simple architecture. Although NeRF has been …
its remarkable quality of rendered images and simple architecture. Although NeRF has been …
Regnerf: Regularizing neural radiance fields for view synthesis from sparse inputs
Abstract Neural Radiance Fields (NeRF) have emerged as a powerful representation for the
task of novel view synthesis due to their simplicity and state-of-the-art performance. Though …
task of novel view synthesis due to their simplicity and state-of-the-art performance. Though …
Contranerf: Generalizable neural radiance fields for synthetic-to-real novel view synthesis via contrastive learning
Although many recent works have investigated generalizable NeRF-based novel view
synthesis for unseen scenes, they seldom consider the synthetic-to-real generalization …
synthesis for unseen scenes, they seldom consider the synthetic-to-real generalization …
NeRF-MS: Neural Radiance Fields with Multi-Sequence
Neural radiance fields (NeRF) achieve impressive performance in novel view synthesis
when trained on only single sequence data. However, leveraging multiple sequences …
when trained on only single sequence data. However, leveraging multiple sequences …
Sparf: Neural radiance fields from sparse and noisy poses
P Truong, MJ Rakotosaona… - Proceedings of the …, 2023 - openaccess.thecvf.com
Abstract Neural Radiance Field (NeRF) has recently emerged as a powerful representation
to synthesize photorealistic novel views. While showing impressive performance, it relies on …
to synthesize photorealistic novel views. While showing impressive performance, it relies on …
NeRF--: Neural radiance fields without known camera parameters
Considering the problem of novel view synthesis (NVS) from only a set of 2D images, we
simplify the training process of Neural Radiance Field (NeRF) on forward-facing scenes by …
simplify the training process of Neural Radiance Field (NeRF) on forward-facing scenes by …
Learning neural duplex radiance fields for real-time view synthesis
Neural radiance fields (NeRFs) enable novel view synthesis with unprecedented visual
quality. However, to render photorealistic images, NeRFs require hundreds of deep …
quality. However, to render photorealistic images, NeRFs require hundreds of deep …
R2L: Distilling Neural Radiance Field to Neural Light Field for Efficient Novel View Synthesis
Recent research explosion on Neural Radiance Field (NeRF) shows the encouraging
potential to represent complex scenes with neural networks. One major drawback of NeRF is …
potential to represent complex scenes with neural networks. One major drawback of NeRF is …
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 …