Mutual Promotion between the Chinese Dream and the Human Rights Protection in China

The Chinese Dream is not only the dream of rejuvenation of the Chinese nation,but also the dream of human rights of the Chinese people.To accurately understand the shared root and origin of the Chinese Dream and the protection of human rights in China,we must understand that the Chinese Dream provides new strategic guidance for the protection of human rights in China,and the protection of human rights in China is an important measure to promote the realization of the Chinese Dream.To realize the Chinese Dream in the new era,Chinass human rights protection must always be people-centered,and adhere to the resolution of the main social contradictions in the new era.On the basis of raising the awareness of the whole Party and society to respect and protect human rights,we should remove obstacles and barriers to human rights protection and promote the building of a community with a shared future for human beings.At the same time,the protection of human rights in China in the new era must be guided by Xi Jinping Thought on Socialism with Chinese Characteristics for a New Era.We must adhere to the path of human rights development with Chinese characteristics,and study and solve various practical problems of human rights protection in China in the course of upholding integrity and innovation,so as to promote the realization of the Chinese Dream.Upholding the leadership of the Communist Party of China is the fundamental guarantee for realizing the Chinese Dream and protecting human rights in China.We must unswervingly follow the CPC’s lead and open up a new stage in the development of Chinas’human rights cause in the new era on the great journey to the Chinese Dream.

Promoting Mutual Learning and Understanding Through Exchanges——Notes on the Visit of the European-American Young Leaders Delegation to China

At the invitation of CAFIU,an 11-member European-American young leaders delegation composed of politicians,think tank researchers and media workers from France,Germany,Italy,UK and US headed by Mr.Manlio di Stefano,Member of House of Representatives of Italy and Chairman of the Five-Star

A People's Gala to Promote Mutual Under standing between China and Other Countries——2012 Understanding and Cooperation Dialogue held by CAFIU

正The Understanding and Cooperation Dialogue, Sponsored by the Chinese Association for International Understanding (CAFIU) and the China Foundation for Peace and Development (CFPD), and Co-organized by the Chinese People' s Association for Peace and

SuperFusion: A Versatile Image Registration and Fusion Network with Semantic Awareness

Image fusion aims to integrate complementary information in source images to synthesize a fused image comprehensively characterizing the imaging scene. However, existing image fusion algorithms are only applicable to strictly aligned source images and cause severe artifacts in the fusion results when input images have slight shifts or deformations. In addition,the fusion results typically only have good visual effect, but neglect the semantic requirements of high-level vision tasks.This study incorporates image registration, image fusion, and semantic requirements of high-level vision tasks into a single framework and proposes a novel image registration and fusion method, named Super Fusion. Specifically, we design a registration network to estimate bidirectional deformation fields to rectify geometric distortions of input images under the supervision of both photometric and end-point constraints. The registration and fusion are combined in a symmetric scheme, in which while mutual promotion can be achieved by optimizing the naive fusion loss, it is further enhanced by the mono-modal consistent constraint on symmetric fusion outputs. In addition, the image fusion network is equipped with the global spatial attention mechanism to achieve adaptive feature integration. Moreover, the semantic constraint based on the pre-trained segmentation model and Lovasz-Softmax loss is deployed to guide the fusion network to focus more on the semantic requirements of high-level vision tasks. Extensive experiments on image registration, image fusion,and semantic segmentation tasks demonstrate the superiority of our Super Fusion compared to the state-of-the-art alternatives.The source code and pre-trained model are publicly available at https://github.com/Linfeng-Tang/Super Fusion.