1 code implementation • 28 Mar 2022 • Shariq Farooq Bhat, Ibraheem Alhashim, Peter Wonka
We build on AdaBins which estimates a global distribution of depth values for the input image and evolve the architecture in two ways.
Ranked #41 on Monocular Depth Estimation on NYU-Depth V2
no code implementations • 4 Jun 2021 • Hiroyasu Akada, Shariq Farooq Bhat, Ibraheem Alhashim, Peter Wonka
Specifically, we extend self-supervised learning from traditional representation learning, which works on images from a single domain, to domain invariant representation learning, which works on images from two different domains by utilizing an image-to-image translation network.
11 code implementations • CVPR 2021 • Shariq Farooq Bhat, Ibraheem Alhashim, Peter Wonka
We address the problem of estimating a high quality dense depth map from a single RGB input image.
Ranked #7 on Depth Estimation on NYU-Depth V2
1 code implementation • 29 Apr 2019 • Anna Frühstück, Ibraheem Alhashim, Peter Wonka
We tackle the problem of texture synthesis in the setting where many input images are given and a large-scale output is required.
45 code implementations • 31 Dec 2018 • Ibraheem Alhashim, Peter Wonka
Accurate depth estimation from images is a fundamental task in many applications including scene understanding and reconstruction.
Ranked #47 on Monocular Depth Estimation on KITTI Eigen split