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GSNeRF: Generalizable Semantic Neural Radiance Fields with Enhanced 3D Scene Understanding
March 7, 2024, 5:42 a.m. | Zi-Ting Chou, Sheng-Yu Huang, I-Jieh Liu, Yu-Chiang Frank Wang
cs.LG updates on arXiv.org arxiv.org
Abstract: Utilizing multi-view inputs to synthesize novel-view images, Neural Radiance Fields (NeRF) have emerged as a popular research topic in 3D vision. In this work, we introduce a Generalizable Semantic Neural Radiance Field (GSNeRF), which uniquely takes image semantics into the synthesis process so that both novel view images and the associated semantic maps can be produced for unseen scenes. Our GSNeRF is composed of two stages: Semantic Geo-Reasoning and Depth-Guided Visual rendering. The former is …
abstract arxiv cs.ai cs.cv cs.lg fields image images inputs nerf neural radiance field neural radiance fields novel popular process research semantic semantics synthesis type understanding view vision work
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