activity
20222025
most citedRadar-Camera Fusion for Object Detection and Semantic Segmentation in Autonomous Driving: A Comprehensive Review

246 citations · 248 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CV2025

Adversarial Attacks on Event-Based Pedestrian Detectors: A Physical Approach

Guixu Lin, Muyao Niu, Qingtian Zhu +4

Event cameras, known for their low latency and high dynamic range, show great potential in pedestrian detection applications. However, while recent research has primarily focused o…

cs.CV2024

Physics-Based Adversarial Attack on Near-Infrared Human Detector for Nighttime Surveillance Camera Systems

Muyao Niu, Zhuoxiao Li, Yifan Zhan +3

Many surveillance cameras switch between daytime and nighttime modes based on illuminance levels. During the day, the camera records ordinary RGB images through an enabled IR-cut f…

cs.CV2024

Motion-Aware Animatable Gaussian Avatars Deblurring

Muyao Niu, Yifan Zhan, Qingtian Zhu +5

The creation of 3D human avatars from multi-view videos is a significant yet challenging task in computer vision. However, existing techniques rely on high-quality, sharp images as…

cs.CV2024

KFD-NeRF: Rethinking Dynamic NeRF with Kalman Filter

Yifan Zhan, Zhuoxiao Li, Muyao Niu +4

We introduce KFD-NeRF, a novel dynamic neural radiance field integrated with an efficient and high-quality motion reconstruction framework based on Kalman filtering. Our key idea i…

cs.CV2024

RS-NeRF: Neural Radiance Fields from Rolling Shutter Images

Muyao Niu, Tong Chen, Yifan Zhan +3

Neural Radiance Fields (NeRFs) have become increasingly popular because of their impressive ability for novel view synthesis. However, their effectiveness is hindered by the Rollin…

cs.CV2023★ 246 cited

Radar-Camera Fusion for Object Detection and Semantic Segmentation in Autonomous Driving: A Comprehensive Review

Shanliang Yao, Runwei Guan, Xiaoyu Huang +8

Driven by deep learning techniques, perception technology in autonomous driving has developed rapidly in recent years, enabling vehicles to accurately detect and interpret surround…