Results 71 to 80 of about 6,226 (231)
Multimodal Human–Robot Interaction Using Human Pose Estimation and Local Large Language Models
Advanced Robotics Research, EarlyView.A multimodal human–robot interaction framework integrates human pose estimation (HPE) and a large language model (LLM) for gesture‐ and voice‐based robot control. Speech‐to‐text (STT) enables voice command interpretation, while a safety‐aware arbitration mechanism prioritizes gesture input for rapid intervention.
Nasiru Aboki +2 more
wiley +1 more source
SELF-SUPERVISED LEARNING FOR MONOCULAR DEPTH ESTIMATION FROM AERIAL IMAGERY [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020 Supervised learning based methods for monocular depth estimation usually require large amounts of extensively annotated training data. In the case of aerial imagery, this ground truth is particularly difficult to acquire.
M. Hermann +7 more
doaj +1 more source
Out-of-Distribution Detection for Monocular Depth Estimation
2023 IEEE/CVF International Conference on Computer Vision (ICCV), 2023 Accepted to ICCV ...
Julia Hornauer +2 more
openaire +2 more sources
Shadow‐Calibrated Stereo Vision for Colorimetric Sweat Analysis
Advanced Science, EarlyView.By establishing a mathematical model that reconstructs 3D structures through geometric features of object shadows under controlled illumination, and combining it with Convolutional Neural Network‐based 2D image analysis for volumetric calibration, this work enables highly accurate 3D morphological reconstruction.
Ting Xiao +7 more
wiley +1 more source
Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference
Advanced Electronic Materials, EarlyView.This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho +6 more
wiley +1 more source
Accurate unsupervised monocular depth estimation for ill-posed region
Frontiers in Physics, 2023 Unsupervised monocular depth estimation is challenging in ill-posed regions, such as weak texture scenes, projection occlusion, and redundant error of detail information, etc.
Xiaofeng Wang +6 more
doaj +1 more source
Self-Supervised Monocular Scene Decomposition and Depth Estimation [PDF]
, 2021 Sadra Safadoust, Fatma Güney
openalex +1 more source
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,
Jinhong Wang +7 more
openaire +2 more sources
Advanced Intelligent Systems, EarlyView.Variational Autoencoder+Deep Deterministic Policy Gradient addresses low‐light failures of infrared depth sensing for indoor robot navigation. Stage 1 pretrains an attention‐enhanced Variational Autoencoder (Convolutional Block Attention Module+Feature Pyramid Network) to map dark depth frames to a well‐lit reconstruction, yielding a 128‐D latent code ...
Uiseok Lee +7 more
wiley +1 more source
Monocular Segment-Wise Depth: Monocular Depth Estimation Based on a Semantic Segmentation Prior [PDF]
2019 IEEE International Conference on Image Processing (ICIP), 2019 Monocular depth estimation using novel learning-based approaches has recently emerged as a promising potential alternative to more conventional 3D scene capture technologies within real-world scenarios. Many such solutions often depend on large quantities of ground truth depth data, which is rare and often intractable to obtain.
Amir Atapour Abarghouei, Toby P. Breckon
openaire +3 more sources