241 citations · 255 across the 11 of their papers we have counts for
11 papers · 1 filter
DeGuNet: Depth-Guided Ultra-Compact Backbones for Efficient LiDAR-Camera 3D Detection
Haifa Zhang, Yijing Wang, Peixi Peng +1
In autonomous driving perception, the fusion of LiDAR and camera modalities has become the dominant paradigm for 3D object detection. However, current multi-modal frameworks heavil…
When Every Millisecond Counts: Real-Time Anomaly Detection via the Multimodal Asynchronous Hybrid Network
Dong Xiao, Guangyao Chen, Peixi Peng +4
Anomaly detection is essential for the safety and reliability of autonomous driving systems. Current methods often focus on detection accuracy but neglect response time, which is c…
CASA: Class-Agnostic Shared Attributes in Vision-Language Models for Efficient Incremental Object Detection
Mingyi Guo, Yuyang Liu, Zhiyuan Yan +3
Incremental object detection is fundamentally challenged by catastrophic forgetting. A major factor contributing to this issue is background shift, where background categories in s…
Sensitivity Decouple Learning for Image Compression Artifacts Reduction
Li Ma, Yifan Zhao, Peixi Peng +1
With the benefit of deep learning techniques, recent researches have made significant progress in image compression artifacts reduction. Despite their improved performances, prevai…
Population-Based Evolutionary Gaming for Unsupervised Person Re-identification
Yunpeng Zhai, Peixi Peng, Mengxi Jia +4
Unsupervised person re-identification has achieved great success through the self-improvement of individual neural networks. However, limited by the lack of diversity of discrimina…
Picking Up Quantization Steps for Compressed Image Classification
Li Ma, Peixi Peng, Guangyao Chen +3
The sensitivity of deep neural networks to compressed images hinders their usage in many real applications, which means classification networks may fail just after taking a screens…