How can we teach humanoids to climb staircases and sit on chairs using thesurrounding environment context? Arguably, the simplest way is to just showthem-casually capture a human motion video and feed it to humanoids. Weintroduce VIDEOMIMIC, a real-to-sim-to-real pipeline that mines everydayvideos, jointly reconstructs the humans and the environment, and produceswhole-body control policies for humanoid robots that perform the correspondingskills. We demonstrate the results of our pipeline on real humanoid robots,showing robust, repeatable contextual control such as staircase ascents anddescents, sitting and standing from chairs and benches, as well as otherdynamic whole-body skills-all from a single policy, conditioned on theenvironment and global root commands. VIDEOMIMIC offers a scalable path towardsteaching humanoids to operate in diverse real-world environments.