Neural Radiance Field (NeRF), a new novel view synthesis with implicit scene
representation has taken the field of Computer Vision by storm. As a novel view synthesis …

Massive data corpora like WebText, Wikipedia, Conceptual Captions, WebImageText, and
LAION have propelled recent dramatic progress in AI. Large neural models trained on such …

We extend neural radiance fields (NeRFs) to dynamic large-scale urban scenes. Prior work
tends to reconstruct single video clips of short durations (up to 10 seconds). Two reasons …

This paper presents a novel grid-based NeRF called F^ 2-NeRF (Fast-Free-NeRF) for novel
view synthesis, which enables arbitrary input camera trajectories and only costs a few …

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

We present an algorithm for reconstructing the radiance field of a large-scale scene from a
single casually captured video. The task poses two core challenges. First, most existing …

Neural radiance fields (NeRFs) refer to a suit of deep neural networks that are used to learn
and represent objects or scenes. Generally speaking, NeRFs have five main characters …

Purely MLP-based neural radiance fields (NeRF-based methods) often suffer from
underfitting with blurred renderings on large-scale scenes due to limited model capacity …

Reconstruction and intrinsic decomposition of scenes from captured imagery would enable
many applications such as relighting and virtual object insertion. Recent NeRF based …

Existing NeRF-based methods for large scene reconstruction often have limitations in visual
quality and rendering speed. While the recent 3D Gaussian Splatting works well on small …