2 papers
cs.CV2026
Adapting Depth Anything to Adverse Imaging Conditions with Events
Shihan Peng, Yuyang Xiong, Hanyu Zhou +5
Robust depth estimation under dynamic and adverse lighting conditions is essential for robotic systems. Currently, depth foundation models, such as Depth Anything, achieve great su…
cs.CV2024
Cycle-YOLO: A Efficient and Robust Framework for Pavement Damage Detection
Zhengji Li, Xi Xiao, Jiacheng Xie +5
With the development of modern society, traffic volume continues to increase in most countries worldwide, leading to an increase in the rate of pavement damage Therefore, the real-…