在AI学术与技术内容发布平台——机器之心的AIxiv专栏，最新报道了一项由中山大学计算机学院研二硕士生陈家豪与导师李冠彬教授共同研究的突破性成果。这项工作围绕神经辐射场（Neural Radiance Fields, NeRF）展开，对去除瞬态干扰物领域进行了深入探索，成功提出了一个无需额外先验知识的启发式引导分割方法。
NeRF自提出以来，以其在新视角合成及三维重建方面的卓越表现，迅速吸引了全球范围内的高度关注。然而，如何有效处理场景中出现的意料之外的干扰物，成为了一个亟待解决的现实问题。陈家豪与李冠彬教授的研究团队，针对这一挑战，创新性地设计了一种基于启发式的分割方法，该方法能够有效去除NeRF建模过程中遇到的瞬态干扰物，显著提升了模型的鲁棒性与泛用性。
该论文作为陈家豪的首个研究成果，充分展示了其在神经渲染和三维重建领域的深厚潜力。而论文的通讯作者李冠彬教授，不仅作为博士生导师，更是中山大学计算机学院、人机物智能融合实验室的领军人物。其团队在视觉感知、场景建模、理解与生成领域有着卓越的学术成就，迄今为止已累计发表CCF A类/中科院一区论文150余篇，Google Scholar引用超过12000次，并曾荣获吴文俊人工智能优秀青年奖等重要荣誉。
这一研究成果的发布，不仅为NeRF领域的研究开辟了新的方向，也为后续相关工作的开展提供了有力的理论与实践支持。对于促进学术交流、推动技术创新具有重要意义，同时也展示了中山大学在计算机科学与人工智能领域的强大科研实力与创新能力。
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英语如下：
News Title: “Sun Yat-sen University Team Breaks New Ground in NeRF Technology, Successfully Eliminates Transient Disturbances”
Keywords: NeRF breakthrough,启发式 segmentation, automated generation
News Content: Title: Sun Yat-sen University Team Achieves New Milestone in NeRF Field, Unveils启发式 Guided Segmentation Method Without Additional Prior Knowledge
In the AI academic and technical content dissemination platform—Machine Intelligence’s AIxiv column, the latest report highlights a groundbreaking achievement by Master’s student, Chen Jiahao, and his supervisor, Professor Li Guanbin, from the Computer Science School of Sun Yat-sen University. This work centers around Neural Radiance Fields (NeRF) and delves into the in-depth exploration of removing transient disturbances, successfully proposing an启发式 guided segmentation method that does not require additional prior knowledge.
Since its introduction, NeRF has garnered global attention for its exceptional performance in synthesizing new perspectives and three-dimensional reconstruction. However, effectively handling unexpected disturbances in the scene has emerged as a pressing challenge. Chen Jiahao and Professor Li Guanbin’s research team innovatively designed a启发式 segmentation method to address this challenge. This method effectively removes transient disturbances encountered during NeRF modeling, significantly enhancing the robustness and versatility of the model.
This paper marks Chen Jiahao’s first research output, showcasing his profound potential in neural rendering and three-dimensional reconstruction. As the corresponding author, Professor Li Guanbin, not only serves as a doctoral supervisor but also leads the School of Computer Science at Sun Yat-sen University and the Lab for Human-Machine-Wearable Intelligence Fusion. His team boasts outstanding academic achievements in visual perception, scene modeling, understanding, and generation, with a total of over 150 CCF A-class/Chinese Academy of Sciences Tier 1 papers published, Google Scholar citations exceeding 12,000, and has been honored with the Wu Wenjun AI Outstanding Young Scholar Award, among other significant accolades.
The release of this research outcome not only opens new directions for NeRF field research but also provides robust theoretical and practical support for subsequent related work. It is of significant importance for facilitating academic exchanges and driving technological innovation. Moreover, it showcases Sun Yat-sen University’s strong research capability and innovative capacity in computer science and artificial intelligence.
If you have outstanding work in this field, you are welcome to submit your work or request coverage through liyazhou@jiqizhixin.com or zhaoyunfeng@jiqizhixin.com to the AIxiv column of Machine Intelligence. Together, we can promote the advancement of academic and technological frontiers.
【来源】https://www.jiqizhixin.com/articles/2024-07-10
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