MMNeRF: Multi-Modal and Multi-View Optimized Cross-Scene Neural Radiance Fields
IEEE Access, 2023 We present MMNeRF, a simple yet powerful learning framework for highly photo-realistic novel view synthesis by learning Multi-modal and Multi-view features to guide neural radiance fields to a generic model.
Qi Zhang +3 more
doaj +1 more source
A Novel H.264/AVC Based Multi-View Video Coding Scheme [PDF]
, 2008 This paper investigates extensions of H.264/AVC for compressing multi-view video sequences. The proposed technique re-sorts frames of sequences captured by multiple cameras looking at a person in a scene from different views and generates a single video ...
Akbari, S +4 more
core +1 more source
On-the-fly Reconstruction for Large-Scale Novel View Synthesis from Unposed Images [PDF]
ACM Transactions on GraphicsRadiance field methods such as 3D Gaussian Splatting (3DGS) allow easy reconstruction from photos, enabling free-viewpoint navigation. Nonetheless, pose estimation using Structure from Motion and 3DGS optimization can still each take between minutes and ...
Andréas Meuleman +4 more
semanticscholar +1 more source
Free3D: Consistent Novel View Synthesis Without 3D Representation [PDF]
Computer Vision and Pattern Recognition, 2023 We introduce Free3D, a simple accurate method for monocular open-set novel view synthesis (NVS). Similar to Zero-1-to-S, we start from a pre-trained 2D image generator for generalization, and fine-tune it for NVS.
Chuanxia Zheng, Andrea Vedaldi
semanticscholar +1 more source
Palette View Synthesis - Novel View Synthesis using Diffusion Probabilistic Modelling [PDF]
, 2023 Novel view synthesis is a class of computer vision problems, in which one or multiple views of a scene or an object are provided. The goal is then to produce novel, previously unseen views of the given scene or object.
Spiegl, Bernard
core
4D-Rotor Gaussian Splatting: Towards Efficient Novel View Synthesis for Dynamic Scenes [PDF]
International Conference on Computer Graphics and Interactive TechniquesWe consider the problem of novel-view synthesis (NVS) for dynamic scenes. Recent neural approaches have accomplished exceptional NVS results for static 3D scenes, but extensions to 4D time-varying scenes remain non-trivial.
Yuanxing Duan +5 more
semanticscholar +1 more source
R2L: Distilling Neural Radiance Field to Neural Light Field for Efficient Novel View Synthesis [PDF]
European Conference on Computer Vision, 2022 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 its prohibitive inference time: Rendering a single pixel requires querying the NeRF ...
Huan Wang +6 more
semanticscholar +1 more source
Dynamic Gaussian Marbles for Novel View Synthesis of Casual Monocular Videos [PDF]
ACM SIGGRAPH Conference and Exhibition on Computer Graphics and Interactive Techniques in AsiaGaussian splatting has become a popular representation for novel-view synthesis, exhibiting clear strengths in efficiency, photometric quality, and compositional edibility.
Colton Stearns +6 more
semanticscholar +1 more source
CompNVS: Novel View Synthesis with Scene Completion
, 2022 We introduce a scalable framework for novel view synthesis from RGB-D images with largely incomplete scene coverage. While generative neural approaches have demonstrated spectacular results on 2D images, they have not yet achieved similar photorealistic results in combination with scene completion where a spatial 3D scene understanding is essential. To
Zuoyue Li +6 more
openaire +3 more sources
FlipNeRF: Flipped Reflection Rays for Few-shot Novel View Synthesis [PDF]
, 2023 Neural Radiance Field (NeRF) has been a mainstream in novel view synthesis with its remarkable quality of rendered images and simple architecture.
Kwak, Nojun +2 more
core +4 more sources