26 datasets found

The Mip-NeRF 360 and Tanks & Temples datasets are used to evaluate the performance of the Pixel-GS method.

EscherNet is a multi-view conditioned diffusion model designed for scalable view synthesis. It leverages Stable Diffusion's 2D architecture empowered by the innovative Camera...

Real-world scenes with reflections, including forward-facing scenes with strong reflection effects caused by glass and mirrors.

A neural scene flow fields for space-time view synthesis of dynamic scenes.

A dataset for training and testing semantically consistent few-shot view synthesis models

A dataset of images of buildings and landmarks, used for training and testing image-based rendering and view synthesis algorithms.

The dataset used in the paper is the LLFF dataset, which contains real-world scenes and is used for training and testing the proposed neural radiance field model.

The dataset used in the paper for omnidirectional Gaussian Splatting for fast radiance field reconstruction using omnidirectional images.

LLFF Real dataset comprises 24 scenes captured from handheld cellphones with 20 − 30 images each.

NeRF realistic synthetic 360° dataset, used for training and testing NeRF models for few-shot view synthesis.

Plenoptic Video Datasets (PVD) is a benchmark dataset for 3D video rendering. It contains challenging volumetric effects, view-dependent effects, and complex actions.

Real-world forward-facing dataset for view synthesis, containing 1008x756 images.

A dataset of synthetic photorealistic images for training and testing material-aware diffusion models

The dataset used in the paper for training and testing the NeRF model.

Soft 3D Reconstruction for View Synthesis

Nex: Real-Time View Synthesis with Neural Basis Expansion

Stereo Magnification: Learning View Synthesis using Multi-Plane Images

NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis

Real-world multi-view datasets DTU and LLFF for view synthesis from sparse inputs.

A point cloud rendering method that achieves comparable rendering performance to NeRF.