Topic: DeepGraphPose

Multi-animal pose estimation is essential for studying animals' social behaviors in neuroscience and neuroethology. Advanced approaches have been proposed to support multi-animal estimation and achieve state-of-the-art performance. However, these models rarely exploit unlabeled data during training even though real-world applications have exponentially more unlabeled frames than labeled frames. Manually adding dense annotations for a large number of images is costly and labor-intensive, especially for multiple instances. To reduce the need for laborious human labeling, we propose a semi-superv