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 …

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

Advancements in 3D scene reconstruction have transformed 2D images from the real world
into 3D models, producing realistic 3D results from hundreds of input photos. Despite great …

Recent developments in differentiable and neural rendering have made impressive
breakthroughs in a variety of 2D and 3D tasks, eg novel view synthesis, 3D reconstruction …

We introduce NoPoSplat, a feed-forward model capable of reconstructing 3D scenes
parameterized by 3D Gaussians from\textit {unposed} sparse multi-view images. Our model …

Gaussian splatting and single/multi-view depth estimation are typically studied in isolation.
In this paper, we present DepthSplat to connect Gaussian splatting and depth estimation …

We introduce MVSplat360, a feed-forward approach for 360 {\deg} novel view synthesis
(NVS) of diverse real-world scenes, using only sparse observations. This setting is …

Reconstructing 3D scenes from multiple viewpoints is a fundamental task in stereo vision.
Recently, advances in generalizable 3D Gaussian Splatting have enabled high-quality …

Realtime 4D reconstruction for dynamic scenes remains a crucial challenge for autonomous
driving perception. Most existing methods rely on depth estimation through self-supervision …

Recent advances in implicit scene representation enable high-fidelity street view novel view
synthesis. However, existing methods optimize a neural radiance field for each scene …