The existing methods fail to effectively utilize the viewpoint information of light field 3D images for watermark embedding which results in a serious decrease in both invisibility and robustness of the watermark. Therefore, we propose a novel, to the best of our knowledge, light field 3D dual-key-based watermarking network (3D-DKWN). Our method employs a pixel mapping algorithm to obtain the disparity sub-image of the light field 3D image and generates an encoding key (EK). Adaptive watermark embedding is then performed on the disparity sub-image and a steganographic key (SK) is generated. Finally, the light field 3D image with the embedded watermark is reconstructed. Compared with previous approaches, our method reasonably utilizes the viewpoint information of light field 3D images, resulting in the significant improvement of invisibility and robustness of the watermark.