3 accepted papers
Object-Goal Navigation (ObjectNav) requires an embodied agent to search for and reach a target object category in previously unseen environments using only onboard egocentric observations, which is a fundamental capability for long-horizon autonomous robots. Current Object-Goal Navigation methods ty…
Current autonomous driving technology typically relies on high-precision (HD) maps to ensure safe, reliable, and accurate navigation in urban environments. While these maps provide essential road information, their creation and maintenance are costly, limiting their widespread application. To mitiga
The Lucas-Kanade (LK) method is a classic iterative homography estimation algorithm for image alignment, but often suffers from poor local optimality especially when image pairs have large distortions. To address this challenge, in this paper we propose a novel Deep Star-Convexified Lucas-Kanade (PR…