5 papers · 1 filter
The Midas Touch for Metric Depth: Interpretable Metricization for Generalizable Depth Perception
Mengtan Zhang, Yu Ma, Shiqi Jiang +6
Recent foundation models have drastically improved the generalization of monocular relative depth estimation, yet recovering accurate metric depth from their estimates for depth pe…
Rebenchmarking Unsupervised Monocular 3D Occupancy Prediction
Zizhan Guo, Yi Feng, Mengtan Zhang +3
Inferring the 3D structure from a single image, particularly in occluded regions, remains a fundamental yet unsolved challenge in vision-centric autonomous driving. Existing unsupe…
Discriminately Treating Motion Components Evolves Joint Depth and Ego-Motion Learning
Mengtan Zhang, Zizhan Guo, Hongbo Zhao +6
Unsupervised learning of depth and ego-motion, two fundamental 3D perception tasks, has made significant strides in recent years. However, most methods treat ego-motion as an auxil…
A Birotation Solution for Relative Pose Problems
Hongbo Zhao, Ziwei Long, Mengtan Zhang +3
Relative pose estimation, a fundamental computer vision problem, has been extensively studied for decades. Existing methods either estimate and decompose the essential matrix or di…
DCPI-Depth: Explicitly Infusing Dense Correspondence Prior to Unsupervised Monocular Depth Estimation
Mengtan Zhang, Yi Feng, Qijun Chen +1
There has been a recent surge of interest in learning to perceive depth from monocular videos in an unsupervised fashion. A key challenge in this field is achieving robust and accu…