| | Portfolio item number 1 tl;dr: Short description of portfolio item number 1  |
Posts by Collection
portfolio
| | Portfolio item number 2 tl;dr: Short description of portfolio item number 2 |
publications
 | DeepFovea: Neural Reconstruction for Foveated Rendering and Video Compression using Learned Statistics of Natural Videos Anton Kaplanyan, Anton Sochenov, Thomas Leimkühler, Mikhail Okunev, Todd Goodall, Gizem Rufo tl;dr: We made a foveated rendering system that allows us to render only ~10% of the pixels, while inpainting the rest with a neural network. SIGGRAPH Asia 2019 [Paper][Project Page] |
 | Spatiotemporally Consistent HDR Indoor Lighting Estimation Zhengqin Li, Li Yu, Mikhail Okunev, Manmohan Chandraker, Zhao Dong tl;dr: Spatially and temporally consistent HDR lighting from videos ACM ToG, Presented in SIGGRAPH Asia 2023 [Paper][Video][Project Page] |
 | F-TöRF: Flowed Time of Flight Radiance Fields Mikhail Okunev*, Marc Mapeke*, Benjamin Attal, Christian Richardt, Matthew O'Toole, James Tompkin tl;dr: C-ToF depth cameras can't reconstruct dynamic objects well. We fix that with our NeRF model that takes raw ToF signal and reconstructs motion along with the depth. All with a static monocular camera! ECCV 2024 [Paper][Project Page] |
 | Monocular Dynamic Gaussian Splatting is Fast and Brittle but Smooth Motion Helps Yiqing Liang, Mikhail Okunev, Mikaela Angelina Uy, Runfeng Li, Leonidas J. Guibas, James Tompkin, Adam Harley tl;dr: We test various SOTA Gaussian Splatting methods for dynamic monocular reconstruction and look at their performance on popular benchmarks. TMLR 2025 [Paper][Project Page] |
 | Time of the Flight of the Gaussians: Fast and Accurate Dynamic Time-of-Flight Radiance Fields Runfeng Li, Mikhail Okunev, Zixuan Guo, Anh Duong, Christian Richardt, Matthew O'Toole, James Tompkin tl;dr: We adapt Gaussian splatting for dynamic continuous-wave time-of-flight radiance fields reconstruction and propose two optimization heuristics that address the discrepancy problem between the rendered mean depth and the depth from rendered raw ToF frames, enabling 100x faster training, >100Hz rendering speed, and more accurate depth. CVPR 2025 [Paper][Project Page] |
talks
| | Talk 1 on Relevant Topic in Your Field tl;dr: This is a description of your talk, which is a markdown files that can be all markdown-ified like any other post. Yay markdown! UC San Francisco, Department of Testing |
| | Tutorial 1 on Relevant Topic in Your Field tl;dr: UC-Berkeley Institute for Testing Science |
| | Talk 2 on Relevant Topic in Your Field tl;dr: London School of Testing |
| | Conference Proceeding talk 3 on Relevant Topic in Your Field tl;dr: This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field. Testing Institute of America 2014 Annual Conference |
teaching
| | Teaching experience 1 tl;dr: This is a description of a teaching experience. You can use markdown like any other post. University 1, Department |
| | Teaching experience 2 tl;dr: This is a description of a teaching experience. You can use markdown like any other post. University 1, Department |