The emergence of 3D Gaussian splatting (3DGS) has greatly accelerated rendering in novel
view synthesis. Unlike neural implicit representations like neural radiance fields (NeRFs) …

Abstract 3D content creation has achieved significant progress in terms of both quality and
speed. Although current feed-forward models can produce 3D objects in seconds, their …

We introduce MVSplat, an efficient model that, given sparse multi-view images as input,
predicts clean feed-forward 3D Gaussians. To accurately localize the Gaussian centers, we …

We present latentSplat, a method to predict semantic Gaussians in a 3D latent space that
can be splatted and decoded by a light-weight generative 2D architecture. Existing methods …

Performing language-conditioned robotic manipulation tasks in unstructured environments
is highly demanded for general intelligent robots. Conventional robotic manipulation …

Radiance field methods have achieved photorealistic novel view synthesis and geometry
reconstruction. But they are mostly applied in per-scene optimization or small-baseline …

Remarkable progress has been made in 4D content generation recently. However, existing
methods suffer from long optimization time, lack of motion controllability, and a low level of …

This paper presents a novel method for building scalable 3D generative models utilizing pre-
trained video diffusion models. The primary obstacle in developing foundation 3D …

Recent techniques for text-to-4D generation synthesize dynamic 3D scenes using
supervision from pre-trained text-to-video models. However, existing representations, such …

3D Gaussian Splatting (3D-GS) has emerged as a significant advancement in the field of
Computer Graphics, offering explicit scene representation and novel view synthesis without …