Self-Sampling for Neural Point Cloud Consolidation

We introduce a novel technique for neural point cloud consolidation which learns from only the input point cloud. Unlike other point up-sampling methods which analyze shapes via local patches, in this work, we learn from global subsets. We repeatedly self-sample the input point cloud with global subsets that are used to train a deep neural network. Specifically, we define source and target subsets according to the desired consolidation criteria (e.g., generating sharp points or points in sparse regions). The network learns a mapping from source to target subsets, and implicitly learns to consolidate the point cloud. During inference, the network is fed with random subsets of points from the input, which it displaces to synthesize a consolidated point set. We leverage the inductive bias of neural networks to eliminate noise and outliers, a notoriously difficult problem in point cloud consolidation. The shared weights of the network are optimized over the entire shape, learning non-local statistics and exploiting the recurrence of local-scale geometries. Specifically, the network encodes the distribution of the underlying shape surface within a fixed set of local kernels, which results in the best explanation of the underlying shape surface. We demonstrate the ability to consolidate point sets from a variety of shapes, while eliminating outliers and noise.

Masculinities and Teacher Education

Teachers’ values and beliefs shape learning environments and reinforce and support their expectations of students’ behaviors. Overtime, students’ behavior undergoes a norming process that influences their understanding of gender roles and gender identity. While there have been political shifts since the early 1980s around gender roles; for many in 2021 these traditional dichotomous notions of gender roles for boys and girls still exist in schools. Many boys are still encouraged to be tough, strong, and emotionally devoid of feelings. For girls, many are encouraged to be polite, sweet, and emotional. Boys are still given a pass for being aggressive, and it is still quite acceptable for girls to be passive. This non-inclusive gender binary continues to damage us as adults and promotes behaviors that do not allow for the complexities regarding gender identity, and then add the factor of race to the mix, and it gets even more complicated and, all of this left unchallenged, can lead to toxic behavior. Various examples of toxic masculinity can be found in the now readily available videos of police officers’ negative engagement with people of color around the globe. Teachers still have tremendous opportunities to intervene and educate students at all levels in ways that embrace difference and create a more empathetic society—will they do it? And what are the implications for changes that must occur in how they are prepared via teacher education programs to work with diverse learners?

Down to earth: Gaia storytelling and the learning organization

Purpose In accordance with Latour, this paper aims to respond to the call for a “down-to-earth” post-learning organization approach to sustainability, which is critical of Senge’s conception of learning organization (LO). Design/methodology/approach “Gaia storytelling” is used to define a LO that is “down to earth.” Findings Gaia is understood through the notion of a critical zone, which foregrounds the local and differentiated terrestrial conditions in which life on Earth is embedded. Practical implications Gaia storytelling implies perceiving LO as a network of storytelling practices enacted and told by unique creative citizens. Such an organization sustains and grows through several entangled storytelling cycles that allow Gaia to shape learning. Social implications The article distinguishes five different storytelling cycles as a way to explore how the Gaia theater cycle connects to other cycles. The four other cycles are called Gaia thinking, explorative, creative and Gaia truth-telling. Originality/value A Gaian LO is a new beginning for LO.