This work presents Depth Anything V2. It significantly outperforms V1 in fine-grained details and robustness. Compared with SD-based models, it enjoys faster inference speed, fewer parameters, and ...

Abstract: In this study, we propose a high-performance disparity (depth) estimation method using dual-pixel (DP) images with few parameters. Conventional end-to-end deep-learning methods have many ...

Desktop CNCs have played an important role in a number of industries, including medicine, electronics, aerospace, and more. These tools help users manufacture products with precision, speed, and ...

Democrats finally opened up to a shutdown. Historically, they have avoided that eventuality at all costs. Times have apparently changed, driven by the fact that a substantial portion of their base is ...

This work presents Video Depth Anything based on Depth Anything V2, which can be applied to arbitrarily long videos without compromising quality, consistency, or generalization ability. Compared with ...

Abstract: Map-free visual relocalization computes camera pose using only a query image and a reference image. Therefore, it is hindered by challenges in feature-point matching and the absence of scale ...