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cs.CV20241 cited

RustNeRF: Robust Neural Radiance Field with Low-Quality Images

Mengfei Li, Ming Lu, Xiaofang Li +1

Recent work on Neural Radiance Fields (NeRF) exploits multi-view 3D consistency, achieving impressive results in 3D scene modeling and high-fidelity novel-view synthesis. However,…

cs.CV2023

A Comprehensive Comparison of Projections in Omnidirectional Super-Resolution

Huicheng Pi, Senmao Tian, Ming Lu +3

Super-Resolution (SR) has gained increasing research attention over the past few years. With the development of Deep Neural Networks (DNNs), many super-resolution methods based on…

cs.CV2022

Uncertainty Guided Depth Fusion for Spike Camera

Jianing Li, Jiaming Liu, Xiaobao Wei +6

Depth estimation is essential for various important real-world applications such as autonomous driving. However, it suffers from severe performance degradation in high-velocity sce…

cs.CV2022

Efficient Meta-Tuning for Content-aware Neural Video Delivery

Xiaoqi Li, Jiaming Liu, Shizun Wang +6

Recently, Deep Neural Networks (DNNs) are utilized to reduce the bandwidth and improve the quality of Internet video delivery. Existing methods train corresponding content-aware su…

cs.CV2022

Structure-aware Editable Morphable Model for 3D Facial Detail Animation and Manipulation

Jingwang Ling, Zhibo Wang, Ming Lu +3

Morphable models are essential for the statistical modeling of 3D faces. Previous works on morphable models mostly focus on large-scale facial geometry but ignore facial details. T…