297 citations · 322 across the 7 of their papers we have counts for
7 papers
DiffBEV: Conditional Diffusion Model for Bird's Eye View Perception
Jiayu Zou, Zheng Zhu, Yun Ye +1
BEV perception is of great importance in the field of autonomous driving, serving as the cornerstone of planning, controlling, and motion prediction. The quality of the BEV feature…
OpenOccupancy: A Large Scale Benchmark for Surrounding Semantic Occupancy Perception
Xiaofeng Wang, Zheng Zhu, Wenbo Xu +7
Semantic occupancy perception is essential for autonomous driving, as automated vehicles require a fine-grained perception of the 3D urban structures. However, existing relevant be…
Are We Ready for Vision-Centric Driving Streaming Perception? The ASAP Benchmark
Xiaofeng Wang, Zheng Zhu, Yunpeng Zhang +5
In recent years, vision-centric perception has flourished in various autonomous driving tasks, including 3D detection, semantic map construction, motion forecasting, and depth esti…
Crafting Monocular Cues and Velocity Guidance for Self-Supervised Multi-Frame Depth Learning
Xiaofeng Wang, Zheng Zhu, Guan Huang +4
Self-supervised monocular methods can efficiently learn depth information of weakly textured surfaces or reflective objects. However, the depth accuracy is limited due to the inher…
MVSTER: Epipolar Transformer for Efficient Multi-View Stereo
Xiaofeng Wang, Zheng Zhu, Fangbo Qin +5
Learning-based Multi-View Stereo (MVS) methods warp source images into the reference camera frustum to form 3D volumes, which are fused as a cost volume to be regularized by subseq…
BEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-View
Junjie Huang, Guan Huang, Zheng Zhu +2
Autonomous driving perceives its surroundings for decision making, which is one of the most complex scenarios in visual perception. The success of paradigm innovation in solving th…
Spot the Difference by Object Detection
Junhui Wu, Yun Ye, Yu Chen +1
In this paper, we propose a simple yet effective solution to a change detection task that detects the difference between two images, which we call "spot the difference". Our approa…