Article
Computer Science, Software Engineering
Jiahui Fan, Beibei Wang, Wenshi Wu, Milos Hasan, Jian Yang, Ling-Qi Yan
Summary: Rendering glinty details from specular microstructure enhances realism in computer graphics. This article proposes a differentiable regularization method to render specular glints, which includes two steps: using differentiable path tracing to render a scene and recording gradients, and predicting the target value by extrapolating the results. The method reduces noise significantly and achieves results close to the reference.
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
(2023)
Article
Computer Science, Software Engineering
Sai Bi, Stephen Lombardi, Shunsuke Saito, Tomas Simon, Shih-En Wei, Kevyn Mcphail, Ravi Ramamoorthi, Yaser Sheikh, Jason Saragih
Summary: A new method is proposed for building high-fidelity animatable 3D face models, combining the strengths of two different training approaches. By training a generalizable but computationally expensive model first, then using it to generate synthetic face images for training, the efficiency of the model is improved while reducing the generalization requirements. The system demonstrates advanced performance in capturing subtle lighting effects and enables face-driven interactions in VR using a photorealistic relightable face model.
ACM TRANSACTIONS ON GRAPHICS
(2021)
Article
Computer Science, Software Engineering
Hong Deng, Yang Liu, Beibei Wang, Jian Yang, Lei Ma, Nicolas Holzschuch, Ling-Qi Yan
Summary: This article presents an efficient method for rendering glinty appearance, achieving constant storage and performance through precomputation and data compression. It is applicable to various practical rendering applications.
ACM TRANSACTIONS ON GRAPHICS
(2022)
Article
Automation & Control Systems
Ali Payami Golhin, Aditya Suneel Sole, Are Strandlie
Summary: This study investigates the color variation based on the texture in an object 3D-printed using the MJT method on a rotary tray. The influence of different parameters on color reproduction accuracy was analyzed, revealing that switching swathes does not affect industrial color matching, but even small thickness variations can lead to unnatural color reproduction. The color differences in most objects might be discernible to inexperienced observers, depending on the 3D printing parameters.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2023)
Article
Computer Science, Software Engineering
Jia-Wun Jhang, Chun-Fa Chang
Summary: This paper proposes an improved version of Specular Manifold Sampling (SMS) called Specular Manifold Bisection Sampling (SMBS), which addresses the issues of the original method when the ray deviates too much from the light or bounces from a complex surface. Experimental results demonstrate that SMBS can find more valid manifold paths in fewer iterations, achieving significant improvement in scenes with complex surfaces.
COMPUTER GRAPHICS FORUM
(2022)
Article
Geochemistry & Geophysics
Tamas Varnai, Alexander Marshak, Alexander B. Kostinski
Summary: This letter provides a wider view on the earlier analyses of observed glints caused by clouds, focusing on how the appearance of these glints varies with wavelength and season. The statistical analysis reveals that the wavelength dependence of glints is mainly shaped by the air above the cloud top, and that the radiative impact of cloud glints displays seasonal variations.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2022)
Article
Computer Science, Software Engineering
B. R. Mallikarjun, Ayush Tewari, Abdallah Dib, Tim Weyrich, Bernd Bickel, Hans-Peter Seidel, Hanspeter Pfister, Wojciech Matusik, Louis Chevallier, Mohamed Elgharib, Christian Theobalt
Summary: This paper presents a method that learns from limited supervised training data for high-quality intuitive editing of camera viewpoint and scene illumination in head portraits; by operating in the generative model space of StyleGAN, combining the best of supervised learning and generative adversarial modeling, it achieves high-quality photorealistic editing of in-the-wild images.
ACM TRANSACTIONS ON GRAPHICS
(2021)
Article
Computer Science, Software Engineering
Steve Bako, Pradeep Sen, Anton Kaplanyan
Summary: This research proposes a comprehensive multi-scale level of detail (LoD) framework for prefiltering 3D environments with complex geometry and materials while maintaining appearance. The approach uses a data-driven prefiltering step to obtain appearance phase function and coverage mask at each scale. A novel neural representation is employed to encode this information for a physically based renderer. The method achieves significant memory savings and compares favorably to state-of-the-art prefiltering methods.
ACM TRANSACTIONS ON GRAPHICS
(2023)
Article
Computer Science, Software Engineering
Donglai Xiang, Timur Bagautdinov, Tuur Stuyck, Fabian Prada, Javier Romero, Weipeng Xu, Shunsuke Saito, Jingfan Guo, Breannan Smith, Takaaki Shiratori, Yaser Sheikh, Jessica Hodgins, Chenglei Wu
Summary: This research introduces pose-driven avatars with explicit modeling of clothing, which exhibit both realistic appearance and dynamic effects. It utilizes a physically-inspired appearance network to generate realistic appearance, even for unseen body-clothing configurations. Thorough evaluation and demonstration of diverse animation results validate the effectiveness of this approach.
ACM TRANSACTIONS ON GRAPHICS
(2022)
Article
Computer Science, Software Engineering
Xilong Zhou, Milos Hasan, Valentin Deschaintre, Paul Guerrero, Kalyan Sunkavalli, Nima Khademi Kalantari
Summary: In this paper, a semi-procedural differentiable material prior is proposed, which represents materials as a set of typically procedural grayscale noises and patterns. This method does not require pre-training on large datasets and achieves single-image tileable material capture comparable with state of the art.
COMPUTER GRAPHICS FORUM
(2023)
Article
Computer Science, Software Engineering
Junqiu Zhu, Sizhe Zhao, Lu Wang, Yanning Xu, Ling-Qi Yan
Summary: This paper proposes an aggregated fur appearance model that accurately describes the optical behavior of a bunch of fur fibers using a single thick cylinder. By reducing the number of fur fibers and utilizing a lightweight neural network, the computational cost is significantly reduced while maintaining realistic fur appearance. The proposed method achieves almost identical results to the ground truth but performs 3.8x to 13.5x faster.
ACM TRANSACTIONS ON GRAPHICS
(2022)
Article
Computer Science, Software Engineering
Rui Yu, Yue Dong, Youkang Kong, Xin Tong
Summary: This method introduces a learning-based approach for efficient rendering of pure specular light transport by training a neural network to model the distribution of all specular light paths between pairs of endpoints, resulting in high-quality results and improved rendering speed.
COMPUTER GRAPHICS FORUM
(2023)
Review
Computer Science, Software Engineering
Junqiu Zhu, Sizhe Zhao, Yanning Xu, Xiangxu Meng, Lu Wang, Ling-Qi Yan
Summary: In this article, we provide a comprehensive survey on recent glinty appearance rendering, starting with a definition based on microfacet theory. We summarize research works in terms of representation and practical rendering, and compare typical methods using a unified platform in terms of visual effects, rendering speed, and memory consumption. We also briefly discuss limitations and future research directions, aiming to provide insight for readers in choosing suitable methods for applications or conducting research.
COMPUTATIONAL VISUAL MEDIA
(2022)
Article
Computer Science, Software Engineering
Shlomi Steinberg, Ling-Qi Yan
Summary: This paper presents the first global light transport framework that takes into account the statistical properties of light and its global evolution, which is fully consistent with Maxwell's electromagnetic theory and retains some attractive properties of traditional radiometry-based light transport.
ACM TRANSACTIONS ON GRAPHICS
(2021)
Article
Physics, Applied
Chenwei Wei, Mengjia Cen, Hsiang-Chen Chui, Tun Cao
Summary: This study introduces a device based on TO technique that can control the propagation direction of surface waves by manipulating the refractive index, providing a new approach to manipulate surface wave propagation.
JOURNAL OF PHYSICS D-APPLIED PHYSICS
(2021)
Article
Computer Science, Software Engineering
Nima Khademi Kalantari, Steve Bako, Pradeep Sen
ACM TRANSACTIONS ON GRAPHICS
(2015)
Article
Computer Science, Software Engineering
Nima Khademi Kalantari, Ting-Chun Wang, Ravi Ramamoorthi
ACM TRANSACTIONS ON GRAPHICS
(2016)
Article
Computer Science, Software Engineering
Alexandr Kuznetsov, Nima Khademi Kalantari, Ravi Ramamoorthi
COMPUTER GRAPHICS FORUM
(2018)
Article
Computer Science, Software Engineering
Nima Khademi Kalantari, Eli Shechtman, Connelly Barnes, Soheil Darabi, Dan B. Goldman, Pradeep Sen
ACM TRANSACTIONS ON GRAPHICS
(2013)
Article
Computer Science, Software Engineering
Nima Khademi Kalantari, Pradeep Sen
COMPUTER GRAPHICS FORUM
(2012)
Article
Computer Science, Software Engineering
Nima Khademi Kalantari, Pradeep Sen
COMPUTER GRAPHICS FORUM
(2013)
Article
Computer Science, Software Engineering
Ben Mildenhall, Pratul P. Srinivasan, Rodrigo Ortiz-Cayon, Nima Khademi Kalantari, Ravi Ramamoorthi, Ren Ng, Abhishek Kar
ACM TRANSACTIONS ON GRAPHICS
(2019)
Article
Computer Science, Software Engineering
Nima Khademi Kalantari, Ravi Ramamoorthi
COMPUTER GRAPHICS FORUM
(2019)
Article
Computer Science, Artificial Intelligence
Avinash Paliwal, Nima Khademi Kalantari
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2020)
Article
Computer Science, Software Engineering
Qinbo Li, Nima Khademi Kalantari
ACM TRANSACTIONS ON GRAPHICS
(2020)
Article
Computer Science, Software Engineering
Xilong Zhou, Nima Khademi Kalantari
Summary: This paper proposes an optimization-based method to estimate the reflectance properties of a near planar surface from a single input image. By introducing a training mechanism and a learned reflectance loss, the overfitting problem of test-time optimization can be addressed. Experimental results demonstrate that the proposed method has good convergence and produces better results.
ACM TRANSACTIONS ON GRAPHICS
(2022)
Article
Computer Science, Software Engineering
N. Milef, S. Sueda, N. Khademi Kalantari
Summary: We propose a learning-based approach for reconstructing full-body pose from sparse upper body tracking data obtained from a virtual reality (VR) device. We use a conditional variational autoencoder with gated recurrent units to synthesize plausible and temporally coherent motions from 4-point tracking. To ensure the plausibility of poses, we introduce a novel sample selection and interpolation strategy with an anomaly detection algorithm. Our system is lightweight, real-time, and capable of producing coherent and realistic motions.
COMPUTER GRAPHICS FORUM
(2023)
Article
Computer Science, Software Engineering
Xilong Zhou, Nima Khademi Kalantari
Summary: This paper proposes a deep learning approach for estimating spatially-varying BRDFs from a single image, overcoming limitations of existing methods by using an adversarial framework and training on both synthetic and real examples. The method shows improved handling of various cases compared to state-of-the-art methods.
COMPUTER GRAPHICS FORUM
(2021)
Article
Computer Science, Software Engineering
Sai Bi, Nima Khademi Kalantari, Ravi Ramamoorthi
ACM TRANSACTIONS ON GRAPHICS
(2017)