4D radar complements dense image semantics with long-range geometry and radial motion, but existing radar--camera detectors largely solve \emph{where} to align the modalities while leaving \emph{whether} a piece of evidence supports an evolving object hypothesis implicit. An image token may describe an occluder, a near...
Xiao-Kai Bai, Zhen-Yu Fan, Lian-Qing Zheng et al.· 0 citations
4D millimeter-wave (mmWave) radar enables all-weather 3D object detection with reliable Doppler sensing. However, its practical application is hindered by inherent sparsity and noise. While multi-frame accumulation densifies point clouds, it inevitably introduces motion-induced spatiotemporal misalignment and geometric...
Xing-Kai Jin, Guang-Xian Xu, Fei Ma et al.· IEEE Robotics and Automation...· 0 citations
Reliable autonomous driving requires full-scene perception that couples foreground objects with dense semantic layout. Recently, 4D millimeter-wave radar has emerged as a robust and affordable sensor, yet its sparse returns make radar-camera fusion necessary for comprehensive scene understanding. Existing radar-camera...
Xiaokai Bai, Lianqing Zheng, Runwei Guan et al.· 0 citations
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