3D LiDAR and Stereo Fusion using Stereo Matching Network with Conditional Cost Volume Normalization

5 Apr 2019Tsun-Hsuan WangHou-Ning HuChieh Hubert LinYi-Hsuan TsaiWei-Chen ChiuMin Sun

The complementary characteristics of active and passive depth sensing techniques motivate the fusion of the Li-DAR sensor and stereo camera for improved depth perception. Instead of directly fusing estimated depths across LiDAR and stereo modalities, we take advantages of the stereo matching network with two enhanced techniques: Input Fusion and Conditional Cost Volume Normalization (CCVNorm) on the LiDAR information... (read more)

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