Results 81 to 90 of about 26,254 (190)

Scalable Autoregressive Monocular Depth Estimation

2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
This paper shows that the autoregressive model is an effective and scalable monocular depth estimator. Our idea is simple: We tackle the monocular depth estimation (MDE) task with an autoregressive prediction paradigm, based on two core designs. First, our depth autoregressive model (DAR) treats the depth map of different resolutions as a set of tokens,
Wang, Jinhong, Liu, Jian, Tang, Dongqi, Wang, Weiqiang, Li, Wentong, Chen, Danny, Chen, Jintai, Wu, Jian   +7 more
openaire   +2 more sources

Revisiting Self-Supervised Monocular Depth Estimation

, 2021
14 pages, 3 figures, 4 ...
Kim, Ue-Hwan, Kim, Jong-Hwan
openaire   +2 more sources

Survey on AI‐Enabled Computer Vision Technologies and Applications for Space Robotic Missions

Journal of Field Robotics, EarlyView.
ABSTRACT This survey provides a comprehensive overview of recent advancements and challenges in Artificial Intelligence (AI)‐enabled computer vision (CV) techniques for space robotic missions, spanning critical phases such as Entry, Descent, and Landing (EDL), orbital operations, and planetary surface exploration.
Maciej Quoos, Steven Kay, Julia Wajoras, Robert Field, Evridiki V. Ntagiou, Fakher Mohammad, Yang Gao   +6 more
wiley   +1 more source

Rotatable Lens‐Based 3D Reconstruction Method for Monocular Vision Systems

SmartBot, EarlyView.
Accurate 3D reconstruction in confined environments remains challenging because conventional vision‐based measurement systems are difficult to maintain compactness without sacrificing accuracy. Here, the authors develop a rotatable lens‐based monocular vision system, which is the first time using the refraction of the light induced by a rotating wedge ...
Puchen Zhu, Zhanpeng Huang, Wenkai Lai, Xiaoyin Zheng, Yiding Nie, Yang Liu, Jiajun An, Daifeng Wang, Dongliang Fan, Xiao Li, Jian S. Dai, Xin Ma   +11 more
wiley   +1 more source

Monocular Absolute Depth Estimation from Motion for Small Unmanned Aerial Vehicles by Geometry-Based Scale Recovery

Sensors
In recent years, there has been extensive research and application of unsupervised monocular depth estimation methods for intelligent vehicles. However, a major limitation of most existing approaches is their inability to predict absolute depth values in
Chuanqi Zhang, Xiangrui Weng, Yunfeng Cao, Meng Ding   +3 more
doaj   +1 more source

Characterising PRPF31‐associated retinal dystrophy: Clinical insights from baseline data in a natural history study

Acta Ophthalmologica, EarlyView.
Abstract Purpose To characterise the baseline clinical features and genotypes of adults with pre‐mRNA processing factor 31 (PRPF31)‐associated retinal dystrophy (RD) enrolled in a prospective, multicentre 4‐year natural history study, and to explore correlations between selected baseline parameters.
Kathrine Olaussen Eriksen, Jon Roger Eidet, Ulrika Kjellström, Jacopo Baldesi, Ragnheidur Bragadóttir, Leonardo Colombo, Josephine Prener Holtan   +6 more
wiley   +1 more source

Determining impact angle from the spatial distribution of shock metamorphism: A case study of the Gosses Bluff (Tnorala) impact structure, Australia

Meteoritics &Planetary Science, EarlyView.
Abstract The majority of planetary impacts occur at oblique angles. Impact structures on Earth are commonly eroded or buried, rendering the identification of the direction and angle of impact—using methods such as asymmetries in ejecta distribution, surface topographic expression, central uplift structure, and geophysical anomalies—challenging. In this
Eloise E. Matthews, Auriol S. P. Rae, Thomas Kenkmann, Nicholas E. Timms, Aaron J. Cavosie, Marian B. Holness   +5 more
wiley   +1 more source

Geo-Temporal Selective Approach for Dynamic Depth Estimation in Outdoor Object Detection and Distance Measurement

IEEE Access
Accurate depth information is crucial for various computer vision applications such as augmented reality, 3D modeling, and autonomous vehicles. Recent advancements have significantly improved both supervised and self-supervised methods for depth ...
Muhammad Faseeh, Misbah Bibi, Murad Ali Khan, Atif Rizwan, Rashid Ahmad, Do Hyeun Kim   +5 more
doaj   +1 more source

Artificial intelligence‐powered plant phenomics: Progress, challenges, and opportunities

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Artificial intelligence (AI), a key driver of the Fourth Industrial Revolution, is being rapidly integrated into plant phenomics to automate sensing, accelerate data analysis, and support decision‐making in phenomic prediction and genomic selection.
Xu Wang, Daeun Choi, Damian Adams, Jaehyun Ahn, Kelly Balmant, Raquel Dias, Carlos D. Messina, Rafael Muñoz‐Carpena, Vance M. Whitaker, Haipeng Yu, Ziwen Yu, Chang Zhao, Changying Li   +12 more
wiley   +1 more source

Improving Operator Depth Vision in Gastrointestinal Endoscopy: A Pilot Study of a New Three‐dimensional Imaging System

DEN Open, Volume 6, Issue 1, April 2026.
ABSTRACT Background and aims Traditional two‐dimensional (2D) gastrointestinal endoscopy lacks depth perception, leading to potential diagnostic errors. This study evaluates a novel software‐based three‐dimensional (3D) endoscopy system that converts 2D images into 3D, compatible with existing endoscopes.
Xiaoqing Lin, Kohei Ono, Ken Ohata, Etsuko Yamabe, Hidenori Eida, Miyuzen Kanamori, Naoki Tomita, Toshifumi Iida, Susumu Banjoya, Tomoya Kimura, Hiroshi Yamazaki, Koichi Furuta, Nao Takeuchi, Yoshiaki Kimoto, Yuki Kano, Yohei Minato, Shunya Takayanagi, Shinya Nagae, Yohei Ito, Ryoju Negishi, Eiji Sakai, Hideyuki Chiba, Zhen Ding   +22 more
wiley   +1 more source