Results 101 to 110 of about 744 (143)

AMENet is a monocular depth estimation network designed for automatic stereoscopic display

Scientific Reports
Monocular depth estimation has a wide range of applications in the field of autostereoscopic displays, while accuracy and robustness in complex scenes are still a challenge.
Tianzhao Wu, Zhongyi Xia, Man Zhou, Ling Bing Kong, Zengyuan Chen   +4 more
doaj   +1 more source

Thermal Image-to-LiDAR Depth Transformation via Pretrained Visual Model and Two-Stage Depth Refinement

Photonics
LiDAR sensors provide reliable physical distance measurements using laser signals, enabling accurate acquisition of 3D information for various optical systems.
HeeJeong Yoo, Hoon Yoo
doaj   +1 more source

Correction to “Enhanced Monocular Depth Estimation Using ResNet Backbone and Multiscale Feature Decoding for Precise Object Distance Measurement”

Advanced Intelligent Systems, EarlyView.
wiley   +1 more source

A Unified Framework for Depth-Assisted Monocular Object Pose Estimation

IEEE Access
Monocular Depth Estimation (MDE) and Object Pose Estimation (OPE) are important tasks in visual scene understanding. Traditionally, these challenges have been addressed independently, with separate deep neural networks designed for each task. However, we
Dinh-Cuong Hoang, Phan Xuan Tan, Thu-Uyen Nguyen, Hai-Nam Pham, Chi-Minh Nguyen, Son-Anh Bui, Quang-Tri Duong, van-Duc Vu, van-Thiep Nguyen, van-Hiep Duong, Ngoc-Anh Hoang, Khanh-Toan Phan, Duc-Thanh Tran, Ngoc-Trung Ho, Cong-Trinh Tran   +14 more
doaj   +1 more source

A simple monocular depth estimation network for balancing complexity and accuracy

Scientific Reports
Monocular depth estimation plays a crucial role in many downstream visual tasks. Although research on monocular depth estimation is relatively mature, it commonly involves strategies that entail increasing both the computational complexity and the number
Xuanxuan Liu, Shuai Tang, Mengdie Feng, Xueqi Guo, Yanru Zhang, Yan Wang   +5 more
doaj   +1 more source

A Monocular Depth Estimation Method for Autonomous Driving Vehicles Based on Gaussian Neural Radiance Fields

Sensors
Monocular depth estimation is one of the key tasks in autonomous driving, which derives depth information of the scene from a single image. And it is a fundamental component for vehicle decision-making and perception.
Ziqin Nie, Zhouxing Zhao, Jieying Pan, Yilong Ren, Haiyang Yu, Liang Xu   +5 more
doaj   +1 more source

Real-time lightweight self-supervised monocular depth estimation

Journal of Measurement Science and Instrumentation
Monocular depth estimation aims to predict depth information within a scene from a single RGB image, but many models remain computationally intensive for real-time inference on resource-constrained edge devices.
YANG Tianxiang, MENG Lingjun, JIN Hong, FENG Wenjie, LIU Xinhao   +4 more
doaj  

Visual Autoregressive Modelling for Monocular Depth Estimation

Proceedings of the 21st International Conference on Computer Vision Theory and Applications
We propose a monocular depth estimation method based on visual autoregressive (VAR) priors, offering an alternative to diffusion-based approaches. Our method adapts a large-scale text-to-image VAR model and introduces a scale-wise conditional upsampling mechanism with classifier-free guidance. Our approach performs inference in ten fixed autoregressive
Amir El-Ghoussani, André Kaup, Nassir Navab, Gustavo Carneiro 0001, Vasileios Belagiannis   +4 more
openaire   +3 more sources

UniDepth: Universal Monocular Metric Depth Estimation

2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Accurate monocular metric depth estimation (MMDE) is crucial to solving downstream tasks in 3D perception and modeling. However, the remarkable accuracy of recent MMDE methods is confined to their training domains. These methods fail to generalize to unseen domains even in the presence of moderate domain gaps, which hinders their practical ...
Piccinelli, Luigi, Yang, Yung-Hsu, Sakaridis, Christos, Segu, Mattia; id_orcid0000-0002-9107-531X, Li, Siyuan, Van Gool, Luc, Yu, Fisher   +6 more
openaire   +4 more sources

Focusable Monocular Depth Estimation

Monocular depth foundation models generalize well across scenes, yet they are typically optimized with uniform pixel-wise objectives that do not distinguish user-specified or task-relevant target regions from the surrounding context. We therefore introduce Focusable Monocular Depth Estimation (FDE), a region-aware depth estimation task in which, given ...
Du, Yuxin, Lin, Tao, Zhong, Zile, Li, Runting, Chen, Xiyao, Liu, Jiting, Liu, Chenglin, Chen, Ying-Cong, Fu, Yuqian, Zhao, Bo   +9 more
openaire   +2 more sources