1 code implementation • 20 Sep 2024 • Sebastian Dille, Chris Careaga, Yağız Aksoy
In this work, we introduce a physically-inspired remodeling of the HDR reconstruction problem in the intrinsic domain.
1 code implementation • ACM Transactions on Graphics 2024 • Chris Careaga, Yağız Aksoy
Intrinsic image decomposition aims to separate the surface reflectance and the effects from the illumination given a single photograph.
no code implementations • 20 Sep 2024 • Sebastian Dille, Ari Blondal, Sylvain Paris, Yağız Aksoy
Class-agnostic image segmentation is a crucial component in automating image editing workflows, especially in contexts where object selection traditionally involves interactive tools.
1 code implementation • 13 Jun 2024 • S. Mahdi H. Miangoleh, Mahesh Reddy, Yağız Aksoy
Existing methods for scale-invariant monocular depth estimation (SI MDE) often struggle due to the complexity of the task, and limited and non-diverse datasets, hindering generalizability in real-world scenarios.
1 code implementation • 6 Dec 2023 • Chris Careaga, S. Mahdi H. Miangoleh, Yağız Aksoy
Despite significant advancements in network-based image harmonization techniques, there still exists a domain disparity between typical training pairs and real-world composites encountered during inference.
2 code implementations • ACM Transactions on Graphics 2023 • Chris Careaga, Yağız Aksoy
We encourage the model to learn an accurate decomposition by computing losses on the estimated shading as well as the albedo implied by the intrinsic model.
1 code implementation • CVPR 2023 • S. Mahdi H. Miangoleh, Zoya Bylinskii, Eric Kee, Eli Shechtman, Yağız Aksoy
We thus offer a viable solution for automating image enhancement and photo cleanup operations.
no code implementations • CVPR 2023 • Sepideh Sarajian Maralan, Chris Careaga, Yağız Aksoy
Flash is an essential tool as it often serves as the sole controllable light source in everyday photography.
1 code implementation • CVPR 2021 • S. Mahdi H. Miangoleh, Sebastian Dille, Long Mai, Sylvain Paris, Yağız Aksoy
Neural networks have shown great abilities in estimating depth from a single image.
Ranked #1 on
Monocular Depth Estimation
on IBims-1
1 code implementation • CVPR 2017 • Yağız Aksoy, Tunç Ozan Aydın, Marc Pollefeys
Our resulting novel linear system formulation can be solved in closed-form and is robust against several fundamental challenges of natural matting such as holes and remote intricate structures.