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In the current era, virtual environments and virtual characters have become popular. In the near future, recognition of virtual facial expressions plays an important role in virtual assistants, online video games, security systems, entertainment, psychological study, video conferencing, virtual reality, and online classes. The objective of this work is to recognize the facial emotions of virtual characters. Facial expression recognition (FER) from virtual characters is a difficult task due to its intra-class variation and inter-class similarity. The performances of existing FER systems are limited in this aspect. To address these challenges, we designed and developed a multi-block deep convolutional neural networks (DCNN) model to recognize the facial emotions from virtual, stylized and human characters. In multi-block DCNN, we defined four blocks with various computational elements to extract the discriminative features …