Boundary between Religion and Social Conflict —Perspective from the Civil Rights Movement

Based on the background of American civil rights movement in which religious factors participated, this study analyzes the function of religious factors in civil rights movement from the perspective of political participation and the principle of separation of politics and religion, in order to consider the research paradigm of the relationship between religion and social conflict. It is believed that religious participation is helpful to exert the positive force of social conflict, the right of religious freedom has, to a certain extent, become the “safety valve” of social stability, and the development of religion is the embodiment of social pluralism and symbiosis

Cascade Residual Learning: A Two-stage Convolutional Neural Network for Stereo Matching

Leveraging on the recent developments in convolutional neural networks (CNNs), matching dense correspondence from a stereo pair has been cast as a learning problem, with performance exceeding traditional approaches. However, it remains challenging to generate high-quality disparities for the inherently ill-posed regions. To tackle this problem, we propose a novel cascade CNN architecture composing of two stages. The first stage advances the recently proposed DispNet by equipping it with extra up-convolution modules, leading to disparity images with more details. The second stage explicitly rectifies the disparity initialized by the first stage; it couples with the first-stage and generates residual signals across multiple scales. The summation of the outputs from the two stages gives the final disparity. As opposed to directly learning the disparity at the second stage, we show that residual learning provides more effective refinement. Moreover, it also benefits the training of the overall cascade network. Experimentation shows that our cascade residual learning scheme provides state-of-the-art performance for matching stereo correspondence. By the time of the submission of this paper, our method ranks first in the KITTI 2015 stereo benchmark, surpassing the prior works by a noteworthy margin.Comment: Accepted at ICCVW 2017. The first two authors contributed equally to this pape