Showing 2026Show all
2 papers · 1 filter
cs.CV2026
DepthAgent: Towards Better Universal Depth Estimation via Sample-wise Expert Selection
Jie Zhu, Girish Chandar Ganesan, Xiaoming Liu
Monocular metric depth estimation has achieved strong progress with large-scale training and universal-camera modeling, yet robust deployment across diverse camera settings, such a…
cs.CV2026
UniDAC: Universal Metric Depth Estimation for Any Camera
Girish Chandar Ganesan, Yuliang Guo, Liu Ren +1
Monocular metric depth estimation (MMDE) is a core challenge in computer vision, playing a pivotal role in real-world applications that demand accurate spatial understanding. Altho…