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오토 인코더 기반 소리 - 이미지 복원 신경망 모델 구현
하현우(Ha Hyunwoo),김성빈(Kim Sungbin),Arda Senocak,오태현(Tae-Hyun Oh) 대한전자공학회 2021 대한전자공학회 학술대회 Vol.2021 No.6
When given an ambient sound, humans can imagine a visual scene corresponding to that sound. In this paper, we study the task of reconstructing a visual scene from an ambient sound. We design and train the deep neural network on AVE dataset to perform this task. During training, our model learns to generate an image embedding from an audio, which then is used to reconstruct an image. By leveraging a pre-trained image decoder, the model is able to reconstruct a high-resolution image on the training set. We evaluate our network qualitatively on seen and unseen dataset and visualize the audio embedding.