no code implementations • ICCV 2023 • Numair Khan, Douglas Lanman, Lei Xiao
Based on the observation that the depth complexity in local image regions is lower than that over the entire image, we split an MPI into many small, tiled regions, each with only a few depth planes.
no code implementations • 18 Dec 2023 • Yiqing Liang, Numair Khan, Zhengqin Li, Thu Nguyen-Phuoc, Douglas Lanman, James Tompkin, Lei Xiao
We propose a method for dynamic scene reconstruction using deformable 3D Gaussians that is tailored for monocular video.
no code implementations • 17 Jan 2024 • Yu-Ying Yeh, Jia-Bin Huang, Changil Kim, Lei Xiao, Thu Nguyen-Phuoc, Numair Khan, Cheng Zhang, Manmohan Chandraker, Carl S Marshall, Zhao Dong, Zhengqin Li
In contrast, TextureDreamer can transfer highly detailed, intricate textures from real-world environments to arbitrary objects with only a few casually captured images, potentially significantly democratizing texture creation.
no code implementations • 31 Jan 2024 • Edward Bartrum, Thu Nguyen-Phuoc, Chris Xie, Zhengqin Li, Numair Khan, Armen Avetisyan, Douglas Lanman, Lei Xiao
We introduce ReplaceAnything3D model (RAM3D), a novel text-guided 3D scene editing method that enables the replacement of specific objects within a scene.
1 code implementation • ICCV 2019 • Numair Khan, Qian Zhang, Lucas Kasser, Henry Stone, Min H. Kim, James Tompkin
Many 4D light field processing applications rely on superpixel segmentations, for which occlusion-aware view consistency is important.
1 code implementation • 9 Sep 2020 • Numair Khan, Min H. Kim, James Tompkin
Previous light field depth estimation methods typically estimate a depth map only for the central sub-aperture view, and struggle with view consistent estimation.
1 code implementation • 7 Jul 2021 • Numair Khan, Min H. Kim, James Tompkin
We present an algorithm to estimate fast and accurate depth maps from light fields via a sparse set of depth edges and gradients.
1 code implementation • CVPR 2021 • Numair Khan, Min H. Kim, James Tompkin
We present a method to estimate dense depth by optimizing a sparse set of points such that their diffusion into a depth map minimizes a multi-view reprojection error from RGB supervision.
1 code implementation • CVPR 2023 • Numair Khan, Eric Penner, Douglas Lanman, Lei Xiao
The presence of dynamic objects further complicates the problem.
1 code implementation • 22 Nov 2021 • Yiheng Xie, Towaki Takikawa, Shunsuke Saito, Or Litany, Shiqin Yan, Numair Khan, Federico Tombari, James Tompkin, Vincent Sitzmann, Srinath Sridhar
Recent advances in machine learning have created increasing interest in solving visual computing problems using a class of coordinate-based neural networks that parametrize physical properties of scenes or objects across space and time.