Deep neural networks (DNNs) have shown remarkable performance improvements on
vision-related tasks such as object detection or image segmentation. Despite their success …

The standard approach to tackling computer vision problems is to train deep convolutional
neural network (CNN) models using large-scale image datasets that are representative of …

[CS482] 3D Gaussian Splatting for Real-Time Radiance Field Rendering Page 1 3D Gaussian
Splatting for Real-Time Radiance Field Rendering November 20, 2023 Bernhard Kerbl …

Abstract Recently 3D Gaussian Splatting has demonstrated impressive novel view synthesis
results reaching high fidelity and efficiency. However strong artifacts can be observed when …

3D Gaussian Splatting (3DGS) has recently revolutionized radiance field reconstruction,
achieving high quality novel view synthesis and fast rendering speed. However, 3DGS fails …

Multi-view stereo reconstruction (MVS) in the wild requires to first estimate the camera
intrinsic and extrinsic parameters. These are usually tedious and cumbersome to obtain yet …

Neural rendering methods have significantly advanced photo-realistic 3D scene rendering
in various academic and industrial applications. The recent 3D Gaussian Splatting method …

We introduce pixelSplat a feed-forward model that learns to reconstruct 3D radiance fields
parameterized by 3D Gaussian primitives from pairs of images. Our model features real-time …

In this work, we investigate the problem of creating high-fidelity 3D content from only a single
image. This is inherently challenging: it essentially involves estimating the underlying 3D …

Abstract We introduce the Splatter Image an ultra-efficient approach for monocular 3D object
reconstruction. Splatter Image is based on Gaussian Splatting which allows fast and high …