Unsupervised Training for 3D Morphable Model Regression

We present a method for training a regression network from image pixels to 3D morphable model coordinates using only unlabeled photographs. The training loss is based on features from a facial recognition network, computed on-the-fly by rendering the predicted faces with a differentiable renderer. To make training from features feasible and avoid network fooling effects, we introduce three objectives: a batch distribution loss that encourages the output distribution to match the distribution of the morphable model, a loopback loss that ensures the network can correctly reinterpret its own output, and a multi-view identity loss that compares the features of the predicted 3D face and the input photograph from multiple viewing angles. We train a regression network using these objectives, a set of unlabeled photographs, and the morphable model itself, and demonstrate state-of-the-art results.Comment: CVPR 2018 version with supplemental material (http://openaccess.thecvf.com/content_cvpr_2018/html/Genova_Unsupervised_Training_for_CVPR_2018_paper.html

Analysis of scattered protons in deuteron electrodisintegration with a polarized electron beam and an internal polarized target

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Physics, 2005.Includes bibliographical references (P. 201-206).Nuclear structure and the underlying internucleon (NN) interaction are central to the understanding of how nucleons interact. However, despite decades of research, Quantum Chromodynamics, which governs the interactions of quarks making up nucleons, continues to evade a fully tractable solution. As a result, understanding of the nucleon and how it interacts with other nucleons is not complete. Due to its simple composition, the deuteron has long been important in understanding the structure of the NN potential. In particular, the tensor asymmetry, Ad, and beam-vector asymmetry, Al, from deuteron electrodisintegration, ... , are sensitive to the existence of a tensor component in the NN interaction. The Bates Large Acceptance Spectrometer Toroid (BLAST) provides a unique opportunity to measure deuteron electrodisintegration asymmetries at low momentum transfer. BLAST combines a high-duty polarized electron beam, an Atomic Beam Source (ABS) target of highly-polarized deuterium atoms, and a large-acceptance spectrometer detector. This work reports on measurements of A.4 and Aid for Q2 ranges between 0.1 and 0.5 (GeV/c)2. Comparisons with Monte Carlo simulations based on the current understanding of the deuteron are made, and conclusions are drawn.by Aaron J. Maschinot.Ph.D

Measurement of the Vector and Tensor Asymmetries at Large Missing Momentum in Quasielastic ([→ over e],e′p) Electron Scattering from Deuterium

We report the measurement of the beam-vector and tensor asymmetries A[subscript ed][superscript V] and A[subscript d][superscript T] in quasielastic ([→ over e],e′p) electrodisintegration of the deuteron at the MIT-Bates Linear Accelerator Center up to missing momentum of 500  MeV/c. Data were collected simultaneously over a momentum transfer range 0.1<Q[superscript 2]<0.5  (GeV/c)[superscript 2] with the Bates Large Acceptance Spectrometer Toroid using an internal deuterium gas target polarized sequentially in both vector and tensor states. The data are compared with calculations. The beam-vector asymmetry A[subscript ed][superscript V] is found to be directly sensitive to the D-wave component of the deuteron and has a zero crossing at a missing momentum of about 320  MeV/c, as predicted. The tensor asymmetry A[subscript d][superscript T] at large missing momentum is found to be dominated by the influence of the tensor force in the neutron-proton final-state interaction. The new data provide a strong constraint on theoretical models