2 citations · 3 across the 10 of their papers we have counts for
10 papers
DINO-VO: Learning Where to Focus for Enhanced State Estimation
Qi Chen, Guanghao Li, Sijia Hu +4
We present DINO Patch Visual Odometry (DINO-VO), an end-to-end monocular visual odometry system with strong scene generalization. Current Visual Odometry (VO) systems often rely on…
Vision-Language Feature Alignment for Road Anomaly Segmentation
Zhuolin He, Jiacheng Tang, Jian Pu +1
Safe autonomous systems in complex environments require robust road anomaly segmentation to identify unknown obstacles. However, existing approaches often rely on pixel-level stati…
Learning Global Representation from Queries for Vectorized HD Map Construction
Shoumeng Qiu, Xinrun Li, Yang Long +3
The online construction of vectorized high-definition (HD) maps is a cornerstone of modern autonomous driving systems. State-of-the-art approaches, particularly those based on the…
Multi-modality Anomaly Segmentation on the Road
Heng Gao, Zhuolin He, Shoumeng Qiu +2
Semantic segmentation allows autonomous driving cars to understand the surroundings of the vehicle comprehensively. However, it is also crucial for the model to detect obstacles th…
PC-BEV: An Efficient Polar-Cartesian BEV Fusion Framework for LiDAR Semantic Segmentation
Shoumeng Qiu, Xinrun Li, XiangYang Xue +1
Although multiview fusion has demonstrated potential in LiDAR segmentation, its dependence on computationally intensive point-based interactions, arising from the lack of fixed cor…
Make a Strong Teacher with Label Assistance: A Novel Knowledge Distillation Approach for Semantic Segmentation
Shoumeng Qiu, Jie Chen, Xinrun Li +3
In this paper, we introduce a novel knowledge distillation approach for the semantic segmentation task. Unlike previous methods that rely on power-trained teachers or other modalit…
Automated Label Unification for Multi-Dataset Semantic Segmentation with GNNs
Rong Ma, Jie Chen, Xiangyang Xue +1
Deep supervised models possess significant capability to assimilate extensive training data, thereby presenting an opportunity to enhance model performance through training on mult…
Towards Camera Open-set 3D Object Detection for Autonomous Driving Scenarios
Zhuolin He, Xinrun Li, Jiacheng Tang +4
Conventional camera-based 3D object detectors in autonomous driving are limited to recognizing a predefined set of objects, which poses a safety risk when encountering novel or uns…
FastOcc: Accelerating 3D Occupancy Prediction by Fusing the 2D Bird's-Eye View and Perspective View
Jiawei Hou, Xiaoyan Li, Wenhao Guan +5
In autonomous driving, 3D occupancy prediction outputs voxel-wise status and semantic labels for more comprehensive understandings of 3D scenes compared with traditional perception…
OpenAnnotate3D: Open-Vocabulary Auto-Labeling System for Multi-modal 3D Data
Yijie Zhou, Likun Cai, Xianhui Cheng +3
In the era of big data and large models, automatic annotating functions for multi-modal data are of great significance for real-world AI-driven applications, such as autonomous dri…