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

We propose GS-LRM, a scalable large reconstruction model that can predict high-quality 3D
Gaussian primitives from 2–4 posed sparse images in\(\sim\) 0.23 s on single A100 GPU …

We present ZeroRF a novel per-scene optimization method addressing the challenge of
sparse view 360deg reconstruction in neural field representations. Current breakthroughs …

Abstract Constructing photo-realistic Free-Viewpoint Videos (FVVs) of dynamic scenes from
multi-view videos remains a challenging endeavor. Despite the remarkable advancements …

We present ZeroRF, a novel per-scene optimization method addressing the challenge of
sparse view 360° reconstruction in neural field representations. Current breakthroughs like …

We present a method for generating high-quality watertight manifold meshes from multi-view
input images. Existing volumetric rendering methods are robust in optimization but tend to …

Despite significant advancements in Neural Radiance Fields (NeRFs), the renderings may
still suffer from aliasing and blurring artifacts, since it remains a fundamental challenge to …

In this paper, we present a novel two-stage approach that fully utilizes the information
provided by the reference image to establish a customized knowledge prior for image-to-3D …

We present IntrinsicAvatar a novel approach to recovering the intrinsic properties of clothed
human avatars including geometry albedo material and environment lighting from only …

Neural radiance fields (NeRF) have achieved great success in novel view synthesis and 3D
representation for static scenarios. Existing dynamic NeRFs usually exploit a locally dense …