Zizhan Guo

2 accepted papers

2026

An Instance-Centric Panoptic Occupancy Prediction Benchmark for Autonomous Driving

Yi Feng, Junwu E, Zizhan Guo, Yu Ma, Hanli Wang, Rui Fan

CVPR 2026

Panoptic occupancy prediction aims to jointly infer voxel-wise semantics and instance identities within a unified 3D scene representation. Nevertheless, progress in this field remains constrained by the absence of high-quality 3D mesh resources, instance-level annotations, and physically consistent

Cited by 1 Source ↗Scholar ↗

2026

The Midas Touch for Metric Depth

Yu Ma, Zizhan Guo, Zuyi Xiong, Haoran Zhang, Yi Feng, Hongbo Zhao +2

CVPR 2026

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, local inconsistencies, and low computational efficiency. To address these issues, we present Midas Touch for Depth (MTD)

Cited by 0 Source ↗code ↗Scholar ↗