Neural Radiance Fields (NeRF) has recently gained popularity for its
impressive novel view synthesis ability. This paper studies the problem of
hallucinated NeRF: i.e., recovering a realistic NeRF at a different time of day
from a group of tourism images. Existing solutions adopt NeRF with a
controllable appearance embedding to render novel views under various
conditions, but they cannot render view-consistent images with an unseen
appearance. To solve this problem, we present an end-to-end framework for
constructing a hallucinated NeRF, dubbed as Ha-NeRF. Specifically, we propose
an appearance hallucination module to handle time-varying appearances and
transfer them to novel views. Considering the complex occlusions of tourism
images, we introduce an anti-occlusion module to decompose the static subjects
for visibility accurately. Experimental results on synthetic data and real
tourism photo collections demonstrate that our method can hallucinate the
desired appearances and render occlusion-free images from different views. The
project and supplementary materials are available at
this https URL

研究 Hallucinated Neural Radiance Fields（Ha-NeRF）的问题，提出一种端到端框架，包括外观幻化模块和反遮挡模块，能够处理旅游照片中存在的外观变化和复杂遮挡，从不同视角生成无遮挡的一致性视图。