  The first Multimodal Emotion Recognition Challenge (MER 2023) was
successfully held at ACM Multimedia. The challenge focuses on system robustness
and consists of three distinct tracks: (1) MER-MULTI, where participants are
required to recognize both discrete and dimensional emotions; (2) MER-NOISE, in
which noise is added to test videos for modality robustness evaluation; (3)
MER-SEMI, which provides a large amount of unlabeled samples for
semi-supervised learning. In this paper, we introduce the motivation behind
this challenge, describe the benchmark dataset, and provide some statistics
about participants. To continue using this dataset after MER 2023, please sign
a new End User License Agreement and send it to our official email address
<EMAIL_ADDRESS>We believe this high-quality dataset can become
a new benchmark in multimodal emotion recognition, especially for the Chinese
research community.
