Monocular depth estimation using deep learning: A review
In current decades, significant advancements in robotics engineering and autonomous
vehicles have improved the requirement for precise depth measurements. Depth estimation …
vehicles have improved the requirement for precise depth measurements. Depth estimation …
Guided depth map super-resolution: A survey
Guided depth map super-resolution (GDSR), which aims to reconstruct a high-resolution
depth map from a low-resolution observation with the help of a paired high-resolution color …
depth map from a low-resolution observation with the help of a paired high-resolution color …
Adding conditional control to text-to-image diffusion models
L Zhang, A Rao, M Agrawala - Proceedings of the IEEE/CVF …, 2023 - openaccess.thecvf.com
We present ControlNet, a neural network architecture to add spatial conditioning controls to
large, pretrained text-to-image diffusion models. ControlNet locks the production-ready large …
large, pretrained text-to-image diffusion models. ControlNet locks the production-ready large …
Depth anything: Unleashing the power of large-scale unlabeled data
Abstract This work presents Depth Anything a highly practical solution for robust monocular
depth estimation. Without pursuing novel technical modules we aim to build a simple yet …
depth estimation. Without pursuing novel technical modules we aim to build a simple yet …
Zoedepth: Zero-shot transfer by combining relative and metric depth
This paper tackles the problem of depth estimation from a single image. Existing work either
focuses on generalization performance disregarding metric scale, ie relative depth …
focuses on generalization performance disregarding metric scale, ie relative depth …
Repurposing diffusion-based image generators for monocular depth estimation
Monocular depth estimation is a fundamental computer vision task. Recovering 3D depth
from a single image is geometrically ill-posed and requires scene understanding so it is not …
from a single image is geometrically ill-posed and requires scene understanding so it is not …
Pretraining is all you need for image-to-image translation
We propose to use pretraining to boost general image-to-image translation. Prior image-to-
image translation methods usually need dedicated architectural design and train individual …
image translation methods usually need dedicated architectural design and train individual …
Metric3d: Towards zero-shot metric 3d prediction from a single image
Reconstructing accurate 3D scenes from images is a long-standing vision task. Due to the ill-
posedness of the single-image reconstruction problem, most well-established methods are …
posedness of the single-image reconstruction problem, most well-established methods are …
P3depth: Monocular depth estimation with a piecewise planarity prior
Monocular depth estimation is vital for scene understanding and downstream tasks. We
focus on the supervised setup, in which ground-truth depth is available only at training time …
focus on the supervised setup, in which ground-truth depth is available only at training time …
Towards robust monocular depth estimation: Mixing datasets for zero-shot cross-dataset transfer
The success of monocular depth estimation relies on large and diverse training sets. Due to
the challenges associated with acquiring dense ground-truth depth across different …
the challenges associated with acquiring dense ground-truth depth across different …