RF-Net: An End-to-End Image Matching Network based on Receptive Field

CVPR 2019 Xuelun ShenCheng WangXin LiZenglei YuJonathan LiChenglu WenMing ChengZijian He

This paper proposes a new end-to-end trainable matching network based on receptive field, RF-Net, to compute sparse correspondence between images. Building end-to-end trainable matching framework is desirable and challenging... (read more)

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