Unsupervised Learning for Robust Fitting:A Reinforcement Learning Approach

Robust model fitting is a core algorithm in a large number of computer vision applications. Solving this problem efficiently for datasets highly contaminated with outliers is, however, still challenging due to the underlying computational complexity. Recent literature has focused on learning-based algorithms. However, most approaches are supervised which require a large amount of labelled training data. In this paper, we introduce a novel unsupervised learning framework that learns to directly solve robust model fitting. Unlike other methods, our work is agnostic to the underlying input features, and can be easily generalized to a wide variety of LP-type problems with quasi-convex residuals. We empirically show that our method outperforms existing unsupervised learning approaches, and achieves competitive results compared to traditional methods on several important computer vision problems.Comment: The preprint of paper accepted to CVPR 202

Deterministic Approximate Methods for Maximum Consensus Robust Fitting

Maximum consensus estimation plays a critically important role in robust fitting problems in computer vision. Currently, the most prevalent algorithms for consensus maximization draw from the class of randomized hypothesize-and-verify algorithms, which are cheap but can usually deliver only rough approximate solutions. On the other extreme, there are exact algorithms which are exhaustive search in nature and can be costly for practical-sized inputs. This paper fills the gap between the two extremes by proposing deterministic algorithms to approximately optimize the maximum consensus criterion. Our work begins by reformulating consensus maximization with linear complementarity constraints. Then, we develop two novel algorithms: one based on non-smooth penalty method with a Frank-Wolfe style optimization scheme, the other based on the Alternating Direction Method of Multipliers (ADMM). Both algorithms solve convex subproblems to efficiently perform the optimization. We demonstrate the capability of our algorithms to greatly improve a rough initial estimate, such as those obtained using least squares or a randomized algorithm. Compared to the exact algorithms, our approach is much more practical on realistic input sizes. Further, our approach is naturally applicable to estimation problems with geometric residual

Temporal and Spatial Regulation of CRE Recombinase Expression in Gonadotrophin-Releasing Hormone Neurones in the Mouse

Gonadotrophin-releasing hormone (GnRH) neurones located within the brain are the final neuroendocrine output regulating the reproductive hormone axis. Their small number and scattered distribution in the hypothalamus make them particularly difficult to study in vivo. The Cre/loxP system is a valuable tool to delete genes in specific cells and tissues. We report the production of two mouse lines that express the CRE bacteriophage recombinase in a GnRH-specific manner. The first line, the GnRH-CRE mouse, contains a transgene in which CRE is under the control of the murine GnRH promoter and targets CRE expression specifically to GnRH neurones in the hypothalamus. The second line, the GnRH-CRETeR mouse, uses the same murine GnRH promoter to target CRE expression to GnRH neurones, but is modified to be constitutively repressed by a tetracycline repressor (TetR) expressed from a downstream tetracycline repressor gene engineered within the transgene. GnRH neurone-specific CRE expression can therefore be induced by treatment with doxycycline which relieves repression by TetR. These GnRH-CRE and GnRH-CRETeR mice can be used to study the function of genes expressed specifically in GnRH neurones. The GnRH-CRETeR mouse can be used to study genes that may have distinct roles in reproductive physiology during the various developmental stages

Measurement of the Lifetime of the Tau Lepton

The tau lepton lifetime is measured with the L3 detector at LEP using the complete data taken at centre-of-mass energies around the Z pole resulting in tau_tau = 293.2 +/- 2.0 (stat) +/- 1.5 (syst) fs. The comparison of this result with the muon lifetime supports lepton universality of the weak charged current at the level of six per mille. Assuming lepton universality, the value of the strong coupling constant, alpha_s is found to be alpha_s(m_tau^2) = 0.319 +/- 0.015(exp.) +/- 0.014 (theory)

Measurement of W Polarisation at LEP

The three different helicity states of W bosons produced in the reaction e+ e- -> W+ W- -> l nu q q~ at LEP are studied using leptonic and hadronic W decays. Data at centre-of-mass energies \sqrt s = 183-209 GeV are used to measure the polarisation of W bosons, and its dependence on the W boson production angle. The fraction of longitudinally polarised W bosons is measured to be 0.218 \pm 0.027 \pm 0.016 where the first uncertainty is statistical and the second systematic, in agreement with the Standard Model expectation

Transplantation of canine umbilical cord blood-derived mesenchymal stem cells in experimentally induced spinal cord injured dogs

This study was to determine the effects of allogenic umbilical cord blood (UCB)-derived mesenchymal stem cells (MSCs) and recombinant methionyl human granulocyte colony-stimulating factor (rmhGCSF) on a canine spinal cord injury model after balloon compression at the first lumbar vertebra. Twenty-five adult mongrel dogs were assigned to five groups according to treatment after a spinal cord injury: no treatment (CN); saline treatment (CP); rmhGCSF treatment (G); UCB-MSCs treatment (UCB-MSC); co-treatment (UCBG). The UCB-MSCs isolated from cord blood of canine fetuses were prepared as 106 cells/150 µl saline. The UCB-MSCs were directly injected into the injured site of the spinal cord and rmhGCSF was administered subcutaneously 1 week after the induction of spinal cord injury. The Olby score, magnetic resonance imaging, somatosensory evoked potentials and histopathological examinations were used to evaluate the functional recovery after transplantation. The Olby scores of all groups were zero at the 0-week evaluation. At 2 week after the transplantation, the Olby scores in the groups with the UCB-MSC and UCBG were significantly higher than in the CN and CP groups. However, there were no significant differences between the UCB-MSC and UCBG groups, and between the CN and CP groups. These comparisons remained stable at 4 and 8 week after transplantation. There was significant improvement in the nerve conduction velocity based on the somatosensory evoked potentials. In addition, a distinct structural consistency of the nerve cell bodies was noted in the lesion of the spinal cord of the UCB-MSC and UCBG groups. These results suggest that transplantation of the UCB-MSCs resulted in recovery of nerve function in dogs with a spinal cord injury and may be considered as a therapeutic modality for spinal cord injury