PXDepth: Pixel-Space Modeling for Structure Preserving Monocular Depth Estimation
Researchers have proposed a new approach to monocular depth estimation called PXDepth. The model separates global context modeling from pixel-level de...
Researchers have proposed a new approach to monocular depth estimation called PXDepth. The model separates global context modeling from pixel-level de...
The article discusses the impact of generative artificial intelligence on journalism. It reviews research from the last two decades and identifies soc...
Researchers have created the YILDIZ-VPR dataset to help improve Visual Place Recognition (VPR) technology. The dataset contains over 12 hours of video...
The 10th AI City Challenge was held in conjunction with ECCV 2026. The challenge has grown over the past decade from a focus on vehicle detection and ...
Researchers have proposed a method for transferring knowledge between large language models using an external memory called Engram. This memory stores...
Researchers have developed a method using large language models to identify protected health information (PHI) in electronic medical records that exis...
Researchers have developed a system called ICD-Deepresearch that can predict which medical diagnosis codes will be documented in a patient's future vi...
Researchers have developed a framework to detect and classify Global Navigation Satellite System (GNSS) spoofing attacks on autonomous vehicles. The s...
Researchers have developed a new framework for node classification in Graph Neural Networks (GNNs). The approach uses minimal abductive explanations a...
Researchers have developed an algorithmic framework called iterative tensor network transformations (ITNTs) to efficiently evaluate nonlinear operatio...
Researchers have proposed a solution to prevent personal language agents from leaking unauthorized information between different audiences. They sugge...
Researchers propose a new framework called QWM that combines Q-learning with world models to improve the performance of reinforcement learning agents....