210 citations · 372 across the 9 of their papers we have counts for
10 papers · 1 filter
Object Concepts Emerge from Motion
Boshi Li, Xiaohui Wang, Xiaoyang Wu +3
Object-centric visual representations are important for physical-world perception, but existing visual pretraining methods often capture semantic categories without preserving the…
Object Concepts Emerge from Motion
Haoqian Liang, Xiaohui Wang, Zhichao Li +2
Object concepts play a foundational role in human visual cognition, enabling perception, memory, and interaction in the physical world. Inspired by findings in developmental neuros…
Lightning NeRF: Efficient Hybrid Scene Representation for Autonomous Driving
Junyi Cao, Zhichao Li, Naiyan Wang +1
Recent studies have highlighted the promising application of NeRF in autonomous driving contexts. However, the complexity of outdoor environments, combined with the restricted view…
Deep Planar Parallax for Monocular Depth Estimation
Haoqian Liang, Zhichao Li, Ya Yang +1
Recent research has highlighted the utility of Planar Parallax Geometry in monocular depth estimation. However, its potential has yet to be fully realized because networks rely hea…
SimpleTrack: Understanding and Rethinking 3D Multi-object Tracking
Ziqi Pang, Zhichao Li, Naiyan Wang
3D multi-object tracking (MOT) has witnessed numerous novel benchmarks and approaches in recent years, especially those under the "tracking-by-detection" paradigm. Despite their pr…
Unsupervised Scale-consistent Depth Learning from Video
Jia-Wang Bian, Huangying Zhan, Naiyan Wang +5
We propose a monocular depth estimator SC-Depth, which requires only unlabelled videos for training and enables the scale-consistent prediction at inference time. Our contributions…
LiDAR R-CNN: An Efficient and Universal 3D Object Detector
Zhichao Li, Feng Wang, Naiyan Wang
LiDAR-based 3D detection in point cloud is essential in the perception system of autonomous driving. In this paper, we present LiDAR R-CNN, a second stage detector that can general…
Model-free Vehicle Tracking and State Estimation in Point Cloud Sequences
Ziqi Pang, Zhichao Li, Naiyan Wang
Estimating the states of surrounding traffic participants stays at the core of autonomous driving. In this paper, we study a novel setting of this problem: model-free single-object…
DMLO: Deep Matching LiDAR Odometry
Zhichao Li, Naiyan Wang
LiDAR odometry is a fundamental task for various areas such as robotics, autonomous driving. This problem is difficult since it requires the systems to be highly robust running in…
Unsupervised Scale-consistent Depth and Ego-motion Learning from Monocular Video
Jia-Wang Bian, Zhichao Li, Naiyan Wang +4
Recent work has shown that CNN-based depth and ego-motion estimators can be learned using unlabelled monocular videos. However, the performance is limited by unidentified moving ob…