Recent advances have shown promise in merging neural radiance fields (NeRFs) with pre-
trained diffusion models for text-to-3D object generation. However, one enduring challenge …

The recent 3D Gaussian splatting (3D-GS) has shown remarkable rendering fidelity and
efficiency compared to NeRF-based neural scene representations. While demonstrating the …

In recent years, Neural Radiance Fields (NeRF) has made remarkable progress in the field
of computer vision and graphics, providing strong technical support for solving key tasks …

3D Gaussian Splatting (3DGS) has emerged as a cutting-edge technique for real-time
radiance field rendering, offering state-of-the-art performance in terms of both quality and …

Referenced-based scene stylization that edits the appearance based on a content-aligned
reference image is an emerging research area. Starting with a pretrained neural radiance …

Following the burgeoning interest in implicit neural representation, Neural Light Field (NeLF)
has been introduced to predict the color of a ray directly. Unlike Neural Radiance Field …

Referenced-based scene stylization that edits the appearance based on a content-aligned
reference image is an emerging research area. Starting with a pretrained neural radiance …

Photographs captured in unstructured tourist environments frequently exhibit variable
appearances and transient occlusions, challenging accurate scene reconstruction and …

Multi-view neural surface reconstruction has exhibited impressive results. However, a
notable limitation is the prohibitively slow inference time when compared to traditional …

We propose Interpretable Neural Radiance Fields (InNeRF) for generalizable 3D scene
representation and rendering. In contrast to previous image-based rendering, which used …