Reconstruction and identification of objects with high transverse momentum (p$_{\mathrm{T}}$), like top quarks and W, Z, Higgs bosons, from their hadronic decays can play a significant role in both searches for new physics and measurements of Standard Model processes at LHC. Cut-based algorithms and recently advanced Machine Learning techniques have been employed to identify and classify hadronic decays of these highly Lorentz-boosted bosons and top quarks. An overview of some of the latest boosted object tagging techniques used by ATLAS and CMS is presented along with their performance on analyses for both experiments.