4 papers
The Midas Touch for Metric Depth
Yu Ma, Zizhan Guo, Zuyi Xiong +5
Recent advances have markedly improved the cross-scene generalization of relative depth estimation, yet its practical applicability remains limited by the absence of metric scale,…
An Instance-Centric Panoptic Occupancy Prediction Benchmark for Autonomous Driving
Yi Feng, Junwu E, Zizhan Guo +3
Panoptic occupancy prediction aims to jointly infer voxel-wise semantics and instance identities within a unified 3D scene representation. Nevertheless, progress in this field rema…
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…