畸变感知的PETR用于混合针孔-鱼眼相机的BEV目标检测
Distortion-Aware PETR for BEV Object Detection with Mixed Pinhole-Fisheye Cameras
AI总结：
针对鱼眼相机径向畸变破坏BEV检测器均匀采样假设的问题，提出DAPETR，通过畸变感知位置编码和双向特征-几何协同调制模块，在KITTI-360基准上优于基线方法，并揭示了学习适应与显式几何重参数化之间的冲突。
摘要：
鱼眼相机因其低成本和高覆盖视野（FOV）而被广泛部署于自动驾驶感知套件中，但其在3D目标检测中的潜力仍未得到充分利用。严重的径向畸变通过违反均匀采样的基本假设，对大多数BEV检测器构成挑战。为弥补这一差距，我们提出了畸变感知PETR（DAPETR），一种专为混合针孔-鱼眼相机设置设计的无投影检测器。DAPETR包含两个关键的学习自适应模块：一个统一的畸变感知位置编码，将图像表示的位置编码与鱼眼几何协调一致；以及一个双向特征-几何协同调制模块，使图像特征和3D位置编码相互适应。在我们转换的KITTI-360基准上的实验中，我们系统地将我们的学习自适应方法与极坐标下的PETR（PolarPETR）进行了比较。我们发现，尽管两种方法都优于基线，但我们的学习模块实现了更优的性能。关键的是，我们发现了两种策略结合时的负面交互，表明学习适应和显式几何重参数化可能冲突。我们的最终DAPETR模型显著推进了鱼眼BEV检测的研究和基准，为除图像校正外的有效畸变感知3D感知设计提供了关键见解。
英文摘要：
Fisheye cameras are widely deployed in autonomous driving perception suites for their low cost and full-coverage field of view (FOV), yet their potential remains underleveraged in 3D object detection. Severe radial distortion challenges most BEV detectors by violating the fundamental assumption of uniform sampling. To bridge this gap, we propose Distortion-Aware PETR (DAPETR), a projection-free detector tailored for mixed pinhole-fisheye camera setups. DAPETR incorporates two key learned-adaptive modules: a unified distortion-aware positional embedding that harmonizes positional encodings for image representations with fisheye geometry, and a bidirectional feature-geometry co-modulation module that mutually adapts image features and 3D positional embeddings. In our experiments on a converted KITTI-360 benchmark, we systematically compare our learned adaptive approach against PETR in polar coordinates (PolarPETR). We find that while both methods improve over the baseline, our learned modules achieve superior performance. Crucially, we uncover a negative interaction when combining both strategies, revealing that learned adaptation and explicit geometric reparameterization can conflict. Our final DAPETR model significantly advances the research and benchmark for fisheye BEV detection, providing critical insights into effective distortion-aware 3D perception design other than image rectification.
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