Neural Rendering
141 papers with code • 0 benchmarks • 7 datasets
Given a representation of a 3D scene of some kind (point cloud, mesh, voxels, etc.), the task is to create an algorithm that can produce photorealistic renderings of this scene from an arbitrary viewpoint. Sometimes, the task is accompanied by image/scene appearance manipulation.
Benchmarks
These leaderboards are used to track progress in Neural Rendering
Libraries
Use these libraries to find Neural Rendering models and implementations
MatrixCity
BUP20
FutureHouse
SB20
DONeRF: Evaluation Dataset
SyntheticFur
ThermoScenes
Latest papers with no code
HashPoint: Accelerated Point Searching and Sampling for Neural Rendering
We solve this problem by our HashPoint method combining these two strategies, leveraging rasterization for efficient point searching and sampling, and ray marching for rendering.
NeRF-DetS: Enhancing Multi-View 3D Object Detection with Sampling-adaptive Network of Continuous NeRF-based Representation
As a preliminary work, NeRF-Det unifies the tasks of novel view synthesis and 3D perception, demonstrating that perceptual tasks can benefit from novel view synthesis methods like NeRF, significantly improving the performance of indoor multi-view 3D object detection.
PGAHum: Prior-Guided Geometry and Appearance Learning for High-Fidelity Animatable Human Reconstruction
In this work, we introduce PGAHum, a prior-guided geometry and appearance learning framework for high-fidelity animatable human reconstruction.
FaceFolds: Meshed Radiance Manifolds for Efficient Volumetric Rendering of Dynamic Faces
3D rendering of dynamic face captures is a challenging problem, and it demands improvements on several fronts$\unicode{x2014}$photorealism, efficiency, compatibility, and configurability.
High-fidelity Endoscopic Image Synthesis by Utilizing Depth-guided Neural Surfaces
In surgical oncology, screening colonoscopy plays a pivotal role in providing diagnostic assistance, such as biopsy, and facilitating surgical navigation, particularly in polyp detection.
Inverse Neural Rendering for Explainable Multi-Object Tracking
We propose to recast 3D multi-object tracking from RGB cameras as an \emph{Inverse Rendering (IR)} problem, by optimizing via a differentiable rendering pipeline over the latent space of pre-trained 3D object representations and retrieve the latents that best represent object instances in a given input image.
RainyScape: Unsupervised Rainy Scene Reconstruction using Decoupled Neural Rendering
We propose RainyScape, an unsupervised framework for reconstructing clean scenes from a collection of multi-view rainy images.
Portrait3D: Text-Guided High-Quality 3D Portrait Generation Using Pyramid Representation and GANs Prior
Existing neural rendering-based text-to-3D-portrait generation methods typically make use of human geometry prior and diffusion models to obtain guidance.
3D Gaussian Splatting as Markov Chain Monte Carlo
While 3D Gaussian Splatting has recently become popular for neural rendering, current methods rely on carefully engineered cloning and splitting strategies for placing Gaussians, which does not always generalize and may lead to poor-quality renderings.
HFNeRF: Learning Human Biomechanic Features with Neural Radiance Fields
In recent advancements in novel view synthesis, generalizable Neural Radiance Fields (NeRF) based methods applied to human subjects have shown remarkable results in generating novel views from few images.
