Cantonese, the second most prevalent Chinese dialect after Mandarin, has been relatively overlooked in machine translation (MT) due to a scarcity of bilingual resources. In this paper, we propose to leverage Mandarin, a high-resource language, as a pivot language for Cantonese-to-English MT. Our method utilizes transfer learning from pre-trained Bidirectional and Auto-Regressive Transformer (BART) models to initialize auxiliary Cantonese-Mandarin and Mandarin-English MT models. The parameters of the auxiliary models are then used to initialize the Cantonese-English model. Based on our experiment, our proposed method outperforms several baseline initialization strategies and naive pivot translation.