Scene Representation Transformer: Geometry-Free Novel View Synthesis Through Set-Latent Scene Representations [PDF]
A classical problem in computer vision is to infer a 3D scene representation from few images that can be used to render novel views at interactive rates. Previous work focuses on reconstructing pre-defined 3D representations, e.g.
Mehdi S. M. Sajjadi +12 more
semanticscholar +1 more source
Re-Nerfing: Improving Novel View Synthesis through Novel View Synthesis
Code will be released upon ...
Tristram, Felix +3 more
openaire +2 more sources
Two-View Mammogram Synthesis from Single-View Data Using Generative Adversarial Networks
While two-view mammography taking both mediolateral-oblique (MLO) and cranio-caudual (CC) views is the current standard method of examination in breast cancer screening, single-view mammography is still being performed in some countries on women of ...
Asumi Yamazaki, Takayuki Ishida
doaj +1 more source
R2L: Distilling Neural Radiance Field to Neural Light Field for Efficient Novel View Synthesis [PDF]
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
Novel View Specification and Synthesis [PDF]
Given a set of real images, Novel View Synthesis (NVS) aims to produce views of a scene that would correspond to that of a virtual camera. There exist many approaches to solving this problem. We consider physically valid NVS methods, in particular those based on epipolar and trifocal transfer.
K. Connor, I. Reid
openaire +1 more source
Novel View Synthesis via Depth-guided Skip Connections [PDF]
We introduce a principled approach for synthesizing new views of a scene given a single source image. Previous methods for novel view synthesis can be divided into image-based rendering methods (e.g. flow prediction) or pixel generation methods. Flow predictions enable the target view to re-use pixels directly, but can easily lead to distorted results.
Solin, Arno, Kannala, Juho, Hou, Yuxin
openaire +3 more sources
STATE: Learning structure and texture representations for novel view synthesis
Novel viewpoint image synthesis is very challenging, especially from sparse views, due to large changes in viewpoint and occlusion. Existing image-based methods fail to generate reasonable results for invisible regions, while geometry-based methods have ...
Xinyi Jing +5 more
doaj +1 more source
Minimal Warping: Planning Incremental Novel‐view Synthesis [PDF]
AbstractObserving that many visual effects (depth‐of‐field, motion blur, soft shadows, spectral effects) and several sampling modalities (time, stereo or light fields) can be expressed as a sum of many pinhole camera images, we suggest a novel efficient image synthesis framework that exploits coherency among those images.
Leimkuehler, T, Seidel, H-P, Ritschel, T
openaire +3 more sources
MMNeRF: Multi-Modal and Multi-View Optimized Cross-Scene Neural Radiance Fields
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
Long-Term Photometric Consistent Novel View Synthesis with Diffusion Models [PDF]
Novel view synthesis from a single input image is a challenging task, where the goal is to generate a new view of a scene from a desired camera pose that may be separated by a large motion.
Jason J. Yu +3 more
semanticscholar +1 more source

