4 accepted papers
Vision Transformers (ViTs) have recently achieved state-of-the-art performance in 2D human pose estimation due to their strong global modeling capability. However, existing ViT-based pose estimators are designed for static images and process each frame independently, thereby ignoring the temporal co
Existing multi-person video pose estimation methods typically adopt a two-stage pipeline: detecting individuals in each frame, followed by temporal modeling for single-person pose estimation. This design relies on heuristic operations such as tracking, RoI cropping, and non-maximum suppression, limi
Academic emotion analysis plays a crucial role in evaluating students' engagement and cognitive states during the learning process. This paper addresses the challenge of automatically recognizing academic emotions through facial expressions in real-world learning environments. While significant prog…
By leveraging temporal dependency in video sequences multi-frame human pose estimation algorithms have demonstrated remarkable results in complicated situations such as occlusion motion blur and video defocus. These algorithms are predominantly based on heatmaps resulting in high computation and sto…