One of the crucial and major issues in engineering, particularly in signal processing, is signal reconstruction. Frames are flexible tools that helps to reconstruct signals/vectors in a stable way. Frame theory was introduced for Hilbert spaces by Duffin et al. in 1952. If it happens that we only have the intensity measurements or the phaseless measurements of the lost signal then reconstructing the original signal becomes difficult. In such cases, phase retrieval sequences play essential roles to reconstruct or regain the signal from its intensity measurements or phaseless measurements. In 2006, Balan et al. introduced phase retrievable frames for Hilbert spaces. Phase retrieval has received significant attention in various fields, including image processing and signal reconstruction. Similar to phase retrieval, norm retrieval sequences help to regain the norm of the original signal. In 2015 Bahmanpour et al. introduced norm retrieval sequences for Hilbert spaces. We provide a thorough overview of phase retrieval and norm retrieval by vectors and subspaces in separable Hilbert space. We also highlight and discuss the recent developments in phase retrieval and norm retrieval of partially lost signals.