Results 11 to 20 of about 849,712 (309)
SparseNeRF: Distilling Depth Ranking for Few-shot Novel View Synthesis [PDF]
Neural Radiance Field (NeRF) significantly degrades when only a limited number of views are available. To complement the lack of 3D information, depth-based models, such as DSNeRF and MonoSDF, explicitly assume the availability of accurate depth maps of ...
Guangcong Wang +3 more
semanticscholar +1 more source
Neural Body: Implicit Neural Representations with Structured Latent Codes for Novel View Synthesis of Dynamic Humans [PDF]
This paper addresses the challenge of novel view synthesis for a human performer from a very sparse set of camera views. Some recent works have shown that learning implicit neural representations of 3D scenes achieves remarkable view synthesis quality ...
Sida Peng +6 more
semanticscholar +1 more source
Compressed 3D Gaussian Splatting for Accelerated Novel View Synthesis [PDF]
Recently, high-fidelity scene reconstruction with an optimized 3D Gaussian splat representation has been introducedfor novel view synthesis from sparse image sets. Making such representations suitable for applications like network streaming and rendering
Simon Niedermayr +2 more
semanticscholar +1 more source
GPS-Gaussian: Generalizable Pixel-Wise 3D Gaussian Splatting for Real-Time Human Novel View Synthesis [PDF]
We present a new approach, termed GPS-Gaussian, for synthesizing novel views of a character in a real-time manner. The proposed method enables 2K-resolution rendering under a sparse-view camera setting.
Shunyuan Zheng +6 more
semanticscholar +1 more source
Accepted at CVPR 2023.
Chen, C +6 more
openaire +2 more sources
Novel-View Human Action Synthesis [PDF]
Asian Conference on Computer Vision (ACCV ...
Lakhal, Mohamed Ilyes +4 more
openaire +2 more sources
The process of synthesizing an image with objects in new pose angles other than input pose is known as Novel View Synthesis. Humans can visualize the objects in new poses by imagination.
Anupama V, A. Geetha Kiran
doaj +1 more source
Complex-Motion NeRF: Joint Reconstruction and Pose Optimization With Motion and Depth Priors
We present Complex-Motion Neural Radiance Fields (CM-NeRF), which is a method that leverages motion and depth priors to optimize neural 3D scene representations and complex 6-DoF camera motions jointly.
Hyunjin Kim +3 more
doaj +1 more source
MINE: Towards Continuous Depth MPI with NeRF for Novel View Synthesis [PDF]
In this paper, we propose MINE to perform novel view synthesis and depth estimation via dense 3D reconstruction from a single image. Our approach is a continuous depth generalization of the Multiplane Images (MPI) by introducing the NEural radiance ...
Jiaxin Li +5 more
semanticscholar +1 more source
Non-Rigid Neural Radiance Fields: Reconstruction and Novel View Synthesis of a Dynamic Scene From Monocular Video [PDF]
We present Non-Rigid Neural Radiance Fields (NR-NeRF), a reconstruction and novel view synthesis approach for general non-rigid dynamic scenes. Our approach takes RGB images of a dynamic scene as input (e.g., from a monocular video recording), and ...
E. Tretschk +5 more
semanticscholar +1 more source

