• The development of DeepLabCut and Social LEAP estimates animal poses and is changing how behavioral research is done by allowing precise and detailed tracking of animal movements. These tools make it possible to study complex behaviors more accurately than traditional observation methods, opening new opportunities for different research fields. • Differences in installation, annotation, and training show that researchers should choose the tool that best matches their technical skills, project goals, and experimental setup. Selecting the appropriate framework enhances research efficiency and accessibility. • The structured annotation methods and evaluation approaches used in both frameworks can help create more consistent and comparable data. This is important for reproducibility and collaboration between different research groups. • Since both frameworks reach similar levels of accuracy, future work can focus more on improving usability, workflows, and adding downstream tasks of interest for the community, making these tools easier to adopt and integrate into different types of research.