3 citations · 9 across the 11 of their papers we have counts for
7 papers · 1 filter
When the Score Becomes the Target: Rethinking Metric Validity in Autonomous Driving
Morui Zhu, Deyuan Qu, Qi Chen +2
Driving benchmark scores are increasingly used not only for evaluation but also as optimization targets. This raises a fundamental question: do score gains remain reliable evidence…
Localization-Guided Foreground Augmentation in Autonomous Driving
Jiawei Yong, Deyuan Qu, Qi Chen +2
Autonomous driving systems often degrade under adverse visibility conditions-such as rain, nighttime, or snow-where online scene geometry (e.g., lane dividers, road boundaries, and…
From Features to Reference Points: Lightweight and Adaptive Fusion for Cooperative Autonomous Driving
Yongqi Zhu, Morui Zhu, Qi Chen +4
We present RefPtsFusion, a lightweight and interpretable framework for cooperative autonomous driving. Instead of sharing large feature maps or query embeddings, vehicles exchange…
HEAD: A Bandwidth-Efficient Cooperative Perception Approach for Heterogeneous Connected and Autonomous Vehicles
Deyuan Qu, Qi Chen, Yongqi Zhu +4
In cooperative perception studies, there is often a trade-off between communication bandwidth and perception performance. While current feature fusion solutions are known for their…
VirtualPainting: Addressing Sparsity with Virtual Points and Distance-Aware Data Augmentation for 3D Object Detection
Sudip Dhakal, Dominic Carrillo, Deyuan Qu +3
In recent times, there has been a notable surge in multimodal approaches that decorates raw LiDAR point clouds with camera-derived features to improve object detection performance.…
Facial Emotion Recognition using CNN in PyTorch
Deyuan Qu, Sudip Dhakal, Dominic Carrillo
In this project, we have implemented a model to recognize real-time facial emotions given the camera images. Current approaches would read all data and input it into their model, w…
SiCP: Simultaneous Individual and Cooperative Perception for 3D Object Detection in Connected and Automated Vehicles
Deyuan Qu, Qi Chen, Tianyu Bai +5
Cooperative perception for connected and automated vehicles is traditionally achieved through the fusion of feature maps from two or more vehicles. However, the absence of feature…