Gameplay Video
Gameplay video analysis is a rapidly evolving field focused on extracting meaningful information and insights from video recordings of gameplay. Current research emphasizes developing AI models, often employing transformer architectures, convolutional neural networks, and recurrent neural networks, to perform tasks such as action recognition, pose estimation, emotion detection, and event segmentation within video sequences. These advancements are driving progress in areas like player experience modeling, video editing and generation, and even applications in healthcare (e.g., pain recognition and ADHD diagnosis) by leveraging the rich spatiotemporal data inherent in gameplay videos. The resulting techniques have significant implications for improving game design, enhancing user experience, and creating new possibilities for human-computer interaction.
Papers
SAM2Point: Segment Any 3D as Videos in Zero-shot and Promptable Manners
Ziyu Guo, Renrui Zhang, Xiangyang Zhu, Chengzhuo Tong, Peng Gao, Chunyuan Li, Pheng-Ann Heng
Exploiting temporal information to detect conversational groups in videos and predict the next speaker
Lucrezia Tosato, Victor Fortier, Isabelle Bloch, Catherine Pelachaud