Exploiting symmetry in structured data is a powerful way to improve the generalization ability, data efficiency, and robustness of AI systems, which leads to the research direction of equivariant deep learning. Showing its effectiveness, it has been widely adopted in a large variety of subareas of computer vision, from 2D image analysis to 3D perception, as well as further applications such as medical imaging and robotics. The workshop will foster discussion and knowledge exchange among researchers actively working on equivariance, providing a platform to share methodologies and explore the latest advancements in this rapidly evolving field.