In the multi-view triangulation with known image observation values and camera internal and external parameters, due to the existence of observation noise, the midpoint method and the L2 back projection standard method have insufficient triangulation accuracy and efficiency, respectively. Therefore, this paper proposes an inverse depth adaptive weihting based multi-view triangulation method. First, by constructing an inverse depth model of the three-dimensional points to be estimated in a multi-view environment, the corresponding weights to the observation errors are assigned under different viewpoints. Then an unbiased estimation model of the approximate angle error for the multi-view triangulation is determined. Finally, a fixed-point iteration is carried out to quickly solve the cost function. Experimental results both on simulation and real datasets show that the proposed method can obtain a better balance between accuracy and efficiency for multi-view triangulation, and the reconstruction accuracy and the number of iterations under different noise conditions are robust.