Zobrazeno 1 - 10
of 185
pro vyhledávání: '"Georgiev, Iliyan"'
We consider bootstrap inference in predictive (or Granger-causality) regressions when the parameter of interest may lie on the boundary of the parameter space, here defined by means of a smooth inequality constraint. For instance, this situation occu
Externí odkaz:
http://arxiv.org/abs/2409.12611
Achieving high efficiency in modern photorealistic rendering hinges on using Monte Carlo sampling distributions that closely approximate the illumination integral estimated for every pixel. Samples are typically generated from a set of simple distrib
Externí odkaz:
http://arxiv.org/abs/2409.18974
Autor:
Cai, Guangyan, Luan, Fujun, Hašan, Miloš, Zhang, Kai, Bi, Sai, Xu, Zexiang, Georgiev, Iliyan, Zhao, Shuang
Glossy objects present a significant challenge for 3D reconstruction from multi-view input images under natural lighting. In this paper, we introduce PBIR-NIE, an inverse rendering framework designed to holistically capture the geometry, material att
Externí odkaz:
http://arxiv.org/abs/2408.06878
We introduce a theoretical and practical framework for efficient importance sampling of mini-batch samples for gradient estimation from single and multiple probability distributions. To handle noisy gradients, our framework dynamically evolves the im
Externí odkaz:
http://arxiv.org/abs/2407.15525
Conventional rendering techniques are primarily designed and optimized for single-frame rendering. In practical applications, such as scene editing and animation rendering, users frequently encounter scenes where only a small portion is modified betw
Externí odkaz:
http://arxiv.org/abs/2406.16302
Autor:
Weier, Philippe, Rath, Alexander, Michel, Élie, Georgiev, Iliyan, Slusallek, Philipp, Boubekeur, Tamy
Publikováno v:
SIGGRAPH Conference Papers '24, July 27-August 1, 2024, Denver, CO, USA
Neural representations have shown spectacular ability to compress complex signals in a fraction of the raw data size. In 3D computer graphics, the bulk of a scene's memory usage is due to polygons and textures, making them ideal candidates for neural
Externí odkaz:
http://arxiv.org/abs/2405.16237
Autor:
Wu, Liwen, Bi, Sai, Xu, Zexiang, Luan, Fujun, Zhang, Kai, Georgiev, Iliyan, Sunkavalli, Kalyan, Ramamoorthi, Ravi
Novel-view synthesis of specular objects like shiny metals or glossy paints remains a significant challenge. Not only the glossy appearance but also global illumination effects, including reflections of other objects in the environment, are critical
Externí odkaz:
http://arxiv.org/abs/2405.14847
Autor:
Zeng, Zheng, Deschaintre, Valentin, Georgiev, Iliyan, Hold-Geoffroy, Yannick, Hu, Yiwei, Luan, Fujun, Yan, Ling-Qi, Hašan, Miloš
Publikováno v:
SIGGRAPH Conference Papers '24, July 27-August 1, 2024, Denver, CO, USA
The three areas of realistic forward rendering, per-pixel inverse rendering, and generative image synthesis may seem like separate and unrelated sub-fields of graphics and vision. However, recent work has demonstrated improved estimation of per-pixel
Externí odkaz:
http://arxiv.org/abs/2405.00666
Machine learning problems rely heavily on stochastic gradient descent (SGD) for optimization. The effectiveness of SGD is contingent upon accurately estimating gradients from a mini-batch of data samples. Instead of the commonly used uniform sampling
Externí odkaz:
http://arxiv.org/abs/2311.14468
Autor:
Korać, Miša, Salaün, Corentin, Georgiev, Iliyan, Grittmann, Pascal, Slusallek, Philipp, Myszkowski, Karol, Singh, Gurprit
Independently estimating pixel values in Monte Carlo rendering results in a perceptually sub-optimal white-noise distribution of error in image space. Recent works have shown that perceptual fidelity can be improved significantly by distributing pixe
Externí odkaz:
http://arxiv.org/abs/2310.02955