Prior-Driven NeRF: Prior Guided Rendering
نویسندگان
چکیده
Neural radiation field (NeRF)-based novel view synthesis methods are gaining popularity. NeRF can generate more detailed and realistic images than traditional methods. Conventional reconstruction of a room scene requires at least several hundred as input data generates spatial sampling points, placing tremendous burden on the training prediction process with respect to memory computational time. To address these problems, we propose prior-driven model that only accepts sparse views reduces significant number non-functional points improve efficiency achieve fast high-quality rendering. First, this study uses depth priors guide sampling, few near controllable range prior used data, which occupation improves prediction. Second, encodes distance weights into guides quickly fit object surface. Finally, approach combining mesh rendering method (TMRM) volume was further efficiency. Experimental results demonstrated our had advantages in case (11 per room) (8 ray).
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ژورنال
عنوان ژورنال: Electronics
سال: 2023
ISSN: ['2079-9292']
DOI: https://doi.org/10.3390/electronics12041014