探索使用DreamGaussian生成濒危物种真实感3D模型的可行性：仰角对模型生成的影响分析
Exploring the Feasibility of Generating Realistic 3D Models of Endangered Species Using DreamGaussian: An Analysis of Elevation Angle's Impact on Model Generation
AI总结：
本研究针对濒危物种数据稀缺的问题，采用零样本稳定扩散模型框架DreamGaussian，探究仰角对单图生成濒危物种逼真3D模型效果的影响，验证了正确仰角可显著提升生成质量，为AI助力濒危物种保护提供参考。
摘要：
许多物种面临灭绝威胁，研究这些物种并尽可能收集相关信息对保护生物多样性至关重要。由于濒危物种的稀有性，可用数据量有限，导致需要数据支撑的生成式AI方法难以应用于该领域。本研究旨在探究利用有限数据生成一致且逼真的濒危动物3D模型的可行性，这一目标促使我们采用零样本stable diffusion（稳定扩散）模型，这类模型可基于目标物种的单张图像生成3D模型。本文聚焦DreamGaussian提出的创新方法，研究仰角与3D模型生成输出质量之间的复杂关联。DreamGaussian是一个采用Generative Gaussian Splatting（生成式高斯溅射）并结合新型网格提取与细化算法的前沿框架，是本研究的核心研究对象。我们开展了全面分析，探究不同仰角对DreamGaussian准确重建3D场景能力的影响。通过实证评估，我们验证了仰角变化如何影响生成图像的空间一致性、结构完整性和感知真实感。研究发现，为输入图像提供正确的仰角会显著影响生成的3D模型效果。我们希望本研究能为AI在濒危动物保护中的可用性提供助力；尽管我们的中期目标是获得一个可通过小样本输出具有生物学一致性3D模型的模型，但对DreamGaussian这类现有最先进模型的定性解读，将是朝着我们目标迈进的一步。
英文摘要：
Many species face the threat of extinction. It's important to study these species and gather information about them as much as possible to preserve biodiversity. Due to the rarity of endangered species, there is a limited amount of data available, making it difficult to apply data requiring generative AI methods to this domain. We aim to study the feasibility of generating consistent and real-like 3D models of endangered animals using limited data. Such a phenomenon leads us to utilize zero-shot stable diffusion models that can generate a 3D model out of a single image of the target species. This paper investigates the intricate relationship between elevation angle and the output quality of 3D model generation, focusing on the innovative approach presented in DreamGaussian. DreamGaussian, a novel framework utilizing Generative Gaussian Splatting along with novel mesh extraction and refinement algorithms, serves as the focal point of our study. We conduct a comprehensive analysis, analyzing the effect of varying elevation angles on DreamGaussian's ability to reconstruct 3D scenes accurately. Through an empirical evaluation, we demonstrate how changes in elevation angle impact the generated images' spatial coherence, structural integrity, and perceptual realism. We observed that giving a correct elevation angle with the input image significantly affects the result of the generated 3D model. We hope this study to be influential for the usability of AI to preserve endangered animals; while the penultimate aim is to obtain a model that can output biologically consistent 3D models via small samples, the qualitative interpretation of an existing state-of-the-art model such as DreamGaussian will be a step forward in our goal.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
