Low axial resolution is a major limitation of fluorescence imaging modalities. We propose a methodology to achieve high isotropic resolution by reconstructing fluorescence volumes from observations of multiple particle replicates with different orientations. The challenge is to conciliate high reconstruction accuracy, requiring a large amount of input 3D data, with computational tractability. We achieve this goal by designing an iterative joint deconvolution and multiview reconstruction algorithm with an efficient augmented-Lagrangian based optimization. The computational cost is limited to only two FFTs per iterations, regardless of the number of input particles. We also adopt the nuclear norm of the Hessian as regularizer to avoid the usual staircase artifacts of the more standard total-variation. Experimental validation on realistic simulated data demonstrate the efficiency and accuracy of our method.