Crowd Datasets

Crowd datasets are collections of images or videos depicting groups of people, used to train and evaluate computer vision algorithms for tasks like crowd counting, density estimation, and 3D crowd reconstruction. Current research focuses on addressing challenges like limited labeled data through data augmentation techniques (e.g., using diffusion models and GANs to generate synthetic data) and improving accuracy in difficult conditions (e.g., low light, occlusion, harsh weather) via image denoising and multimodal data fusion. These advancements are crucial for improving the safety and efficiency of crowd management systems, enabling better understanding of crowd behavior, and advancing research in areas such as anomaly detection and human-computer interaction.