Photo-Realistic Facial Details Synthesis from Single Image
Conference Proceeding
Chen, A., Chen, Z., Zhang, G., Zhang, Z., Mitchell, K., & Yu, J. (2019)
Photo-Realistic Facial Details Synthesis from Single Image. In 2019 IEEE/CVF International Conference on Computer Vision (ICCV) (9429-9439). https://doi.org/10.1109/ICCV.2019.00952
We present a single-image 3D face synthesis technique that can handle challenging facial expressions while recovering fine geometric details. Our technique employs expression ...
Enhanced Shadow Retargeting with Light-Source Estimation Using Flat Fresnel Lenses
Journal Article
Casas, L., Fauconneau, M., Kosek, M., Mclister, K., & Mitchell, K. (2019)
Enhanced Shadow Retargeting with Light-Source Estimation Using Flat Fresnel Lenses. Computers, 8(2), https://doi.org/10.3390/computers8020029
Shadow-retargeting maps depict the appearance of real shadows to virtual shadows given corresponding deformation of scene geometry, such that appearance is seamlessly maintain...
Real-time rendering with compressed animated light fields.
Conference Proceeding
Koniaris, B., Kosek, M., Sinclair, D., & Mitchell, K. (2017)
Real-time rendering with compressed animated light fields. In GI '17 Proceedings of the 43rd Graphics Interface Conference. , (33-40). https://doi.org/10.20380/GI2017.05
We propose an end-to-end solution for presenting movie quality animated graphics to the user while still allowing the sense of presence afforded by free viewpoint head motion....
Real-Time Multi-View Facial Capture with Synthetic Training
Journal Article
Klaudiny, M., McDonagh, S., Bradley, D., Beeler, T., & Mitchell, K. (2017)
Real-Time Multi-View Facial Capture with Synthetic Training. Computer Graphics Forum, 36(2), 325-336. https://doi.org/10.1111/cgf.13129
We present a real-time multi-view facial capture system facilitated by synthetic training imagery. Our method is able to achieve high-quality markerless facial performance cap...
Noise Reduction on G-Buffers for Monte Carlo Filtering: Noise Reduction on G-Buffers for Monte Carlo Filtering
Journal Article
Moon, B., Iglesias-Guitian, J. A., McDonagh, S., & Mitchell, K. (2017)
Noise Reduction on G-Buffers for Monte Carlo Filtering: Noise Reduction on G-Buffers for Monte Carlo Filtering. Computer Graphics Forum, 36(8), 600-612. https://doi.org/10.1111/cgf.13155
We propose a novel pre-filtering method that reduces the noise introduced by depth-of-field and motion blur effects in geometric
buffers (G-buffers) such as texture, normal an...
Rapid one-shot acquisition of dynamic VR avatars
Conference Proceeding
Malleson, C., Kosek, M., Klaudiny, M., Huerta, I., Bazin, J., Sorkine-Hornung, A., …Mitchell, K. (2017)
Rapid one-shot acquisition of dynamic VR avatars. In IEEE 2017 Virtual Reality (VR). https://doi.org/10.1109/vr.2017.7892240
We present a system for rapid acquisition of bespoke, animatable, full-body avatars including face texture and shape. A blendshape rig with a skeleton is used as a template fo...
Synthetic Prior Design for Real-Time Face Tracking
Conference Proceeding
McDonagh, S., Klaudiny, M., Bradley, D., Beeler, T., Matthews, I., & Mitchell, K. (2016)
Synthetic Prior Design for Real-Time Face Tracking. In 2016 Fourth International Conference on 3D Vision (3DV),. https://doi.org/10.1109/3dv.2016.72
Real-time facial performance capture has recently been gaining popularity in virtual film production, driven by advances in machine learning, which allows for fast inference o...
Real-time Physics-based Motion Capture with Sparse Sensors
Conference Proceeding
Andrews, S., Huerta, I., Komura, T., Sigal, L., & Mitchell, K. (2016)
Real-time Physics-based Motion Capture with Sparse Sensors. In Proceedings of the 13th European Conference on Visual Media Production (CVMP 2016)https://doi.org/10.1145/2998559.2998564
We propose a framework for real-time tracking of humans using sparse multi-modal sensor sets, including data obtained from optical markers and inertial measurement units. A sm...
Pixel history linear models for real-time temporal filtering.
Journal Article
Iglesias-Guitian, J. A., Moon, B., Koniaris, C., Smolikowski, E., & Mitchell, K. (2016)
Pixel history linear models for real-time temporal filtering. Computer Graphics Forum, 35(7), 363-372. https://doi.org/10.1111/cgf.13033
We propose a new real-time temporal filtering and antialiasing (AA) method for rasterization graphics pipelines. Our method is based on Pixel History Linear Models (PHLM), a n...
Nonlinearly Weighted First-order Regression for Denoising Monte Carlo Renderings
Journal Article
Bitterli, B., Rousselle, F., Moon, B., Iglesias-Guitián, J. A., Adler, D., Mitchell, K., …Novák, J. (2016)
Nonlinearly Weighted First-order Regression for Denoising Monte Carlo Renderings. Computer Graphics Forum, 35(4), 107-117. https://doi.org/10.1111/cgf.12954
We address the problem of denoising Monte Carlo renderings by studying existing approaches and proposing a new algorithm that yields state-of-the-art performance on a wide ran...