1 code implementation • 23 Apr 2024 • Cameron Smith, David Charatan, Ayush Tewari, Vincent Sitzmann
This paper introduces FlowMap, an end-to-end differentiable method that solves for precise camera poses, camera intrinsics, and per-frame dense depth of a video sequence.
no code implementations • 8 Dec 2023 • Jaskirat Singh, Jianming Zhang, Qing Liu, Cameron Smith, Zhe Lin, Liang Zheng
To overcome these limitations, we introduce SmartMask, which allows any novice user to create detailed masks for precise object insertion.
1 code implementation • CVPR 2023 • Yilun Du, Cameron Smith, Ayush Tewari, Vincent Sitzmann
We conduct extensive comparisons on held-out test scenes across two real-world datasets, significantly outperforming prior work on novel view synthesis from sparse image observations and achieving multi-view-consistent novel view synthesis.
no code implementations • 9 Feb 2023 • Yiran Xu, Zhixin Shu, Cameron Smith, Seoung Wug Oh, Jia-Bin Huang
3D-aware GANs offer new capabilities for view synthesis while preserving the editing functionalities of their 2D counterparts.
no code implementations • 2 Feb 2023 • Ximo Pechuan-Jorge, Raymond S. Puzio, Cameron Smith
Crucially, we identify the fact that the Lie group associated to hierarchic reaction networks decomposes as a wreath product of the groups associated to the subnetworks of the independent and dependent types.
no code implementations • ICCV 2023 • Manuel Ladron De Guevara, Jose Echevarria, Yijun Li, Yannick Hold-Geoffroy, Cameron Smith, Daichi Ito
We present a novel method for automatic vectorized avatar generation from a single portrait image.
1 code implementation • 17 Aug 2022 • Jaskirat Singh, Liang Zheng, Cameron Smith, Jose Echevarria
In particular, we propose a novel approach paint2pix, which learns to predict (and adapt) "what a user wants to draw" from rudimentary brushstroke inputs, by learning a mapping from the manifold of incomplete human paintings to their realistic renderings.
no code implementations • 8 May 2022 • Cameron Smith, Hong-Xing Yu, Sergey Zakharov, Fredo Durand, Joshua B. Tenenbaum, Jiajun Wu, Vincent Sitzmann
Neural scene representations, both continuous and discrete, have recently emerged as a powerful new paradigm for 3D scene understanding.
no code implementations • 16 Dec 2021 • Jaskirat Singh, Cameron Smith, Jose Echevarria, Liang Zheng
However, current research in this direction is often reliant on a progressive grid-based division strategy wherein the agent divides the overall image into successively finer grids, and then proceeds to paint each of them in parallel.
no code implementations • 20 Jun 2021 • Gerald M Pao, Cameron Smith, Joseph Park, Keichi Takahashi, Wassapon Watanakeesuntorn, Hiroaki Natsukawa, Sreekanth H Chalasani, Tom Lorimer, Ryousei Takano, Nuttida Rungratsameetaweemana, George Sugihara
Thus, as a final validation of how well GMN captures essential dynamic information, we show that the artificially generated time series can be used as a training set to predict out-of-sample observed fly locomotion, as well as brain activity in out of sample withheld data not used in model building.
no code implementations • 30 Sep 2020 • Yu Guo, Cameron Smith, Miloš Hašan, Kalyan Sunkavalli, Shuang Zhao
We address the problem of reconstructing spatially-varying BRDFs from a small set of image measurements.