Zobrazeno 1 - 10
of 361
pro vyhledávání: '"Guo, Yanwen"'
Recently, 3D Gaussian Splatting (3D-GS) has achieved impressive results in novel view synthesis, demonstrating high fidelity and efficiency. However, it easily exhibits needle-like artifacts, especially when increasing the sampling rate. Mip-Splattin
Externí odkaz:
http://arxiv.org/abs/2409.12771
Implicit Neural Representation (INR), which utilizes a neural network to map coordinate inputs to corresponding attributes, is causing a revolution in the field of signal processing. However, current INR techniques suffer from the "frequency"-specifi
Externí odkaz:
http://arxiv.org/abs/2407.19434
Autor:
Fan, Zhimin, Guo, Jie, Wang, Yiming, Xiao, Tianyu, Zhang, Hao, Zhou, Chenxi, Chen, Zhenyu, Hong, Pengpei, Guo, Yanwen, Yan, Ling-Qi
Finding valid light paths that involve specular vertices in Monte Carlo rendering requires solving many non-linear, transcendental equations in high-dimensional space. Existing approaches heavily rely on Newton iterations in path space, which are lim
Externí odkaz:
http://arxiv.org/abs/2405.13409
The field of 3D detailed human mesh reconstruction has made significant progress in recent years. However, current methods still face challenges when used in industrial applications due to unstable results, low-quality meshes, and a lack of UV unwrap
Externí odkaz:
http://arxiv.org/abs/2403.02561
3D Gaussian Splatting (3D-GS) has recently attracted great attention with real-time and photo-realistic renderings. This technique typically takes perspective images as input and optimizes a set of 3D elliptical Gaussians by splatting them onto the i
Externí odkaz:
http://arxiv.org/abs/2402.00763
3D Gaussian Splatting has garnered extensive attention and application in real-time neural rendering. Concurrently, concerns have been raised about the limitations of this technology in aspects such as point cloud storage, performance, and robustness
Externí odkaz:
http://arxiv.org/abs/2402.00752
Implicit Neural Representation (INR), which utilizes a neural network to map coordinate inputs to corresponding attributes, is causing a revolution in the field of signal processing. However, current INR techniques suffer from a restricted capability
Externí odkaz:
http://arxiv.org/abs/2312.02434
Complex visual effects such as caustics are often produced by light paths containing multiple consecutive specular vertices (dubbed specular chains), which pose a challenge to unbiased estimation in Monte Carlo rendering. In this work, we study the l
Externí odkaz:
http://arxiv.org/abs/2311.12818
Rainy weather significantly deteriorates the visibility of scene objects, particularly when images are captured through outdoor camera lenses or windshields. Through careful observation of numerous rainy photos, we have found that the images are gene
Externí odkaz:
http://arxiv.org/abs/2303.17766
Predicting panoramic indoor lighting from a single perspective image is a fundamental but highly ill-posed problem in computer vision and graphics. To achieve locale-aware and robust prediction, this problem can be decomposed into three sub-tasks: de
Externí odkaz:
http://arxiv.org/abs/2303.10344