The computer graphics and computer vision communities have been working closely together in recent years and a variety of algorithms and applications have been developed to analyze and manipulate the visual media arou...The computer graphics and computer vision communities have been working closely together in recent years and a variety of algorithms and applications have been developed to analyze and manipulate the visual media around us. There are three major driving forces behind this phenomenon： 1） the availability of big data from the Internet has created a demand for dealing with the ever-increasing, vast amount of resources; 2） powerful processing tools, such as deep neural networks, provide effective ways for learning how to deal with heterogeneous visual data; 3） new data capture devices, such as the Kilxect, the bridge betweea algorithms for 2D image understanding and 3D model analysis. These driving forces have emerged only recently, and we believe that the computer graphics and computer vision communities are still in the beginning of their honeymoon phase. In this work we survey recent research on how computer vision techniques benefit computer graphics techniques and vice versa, and cover research on analysis, manipulation, synthesis, and interaction. We also discuss existing problems and suggest possible further research directions.展开更多
基金This research was sponsored by the National Natural Science Foundation of China under Grant Nos. 61572264 and 61373069, the National Key Research and Development Plan of China under Grant No. 2016YFB1001402, Huawei Innovation Research Program （HIRP）, China Association for Science and Technology （CAST） Young Talents Plan, and Tianjin Short-Term Recruitment Program of Foreign Experts.
文摘The computer graphics and computer vision communities have been working closely together in recent years and a variety of algorithms and applications have been developed to analyze and manipulate the visual media around us. There are three major driving forces behind this phenomenon： 1） the availability of big data from the Internet has created a demand for dealing with the ever-increasing, vast amount of resources; 2） powerful processing tools, such as deep neural networks, provide effective ways for learning how to deal with heterogeneous visual data; 3） new data capture devices, such as the Kilxect, the bridge betweea algorithms for 2D image understanding and 3D model analysis. These driving forces have emerged only recently, and we believe that the computer graphics and computer vision communities are still in the beginning of their honeymoon phase. In this work we survey recent research on how computer vision techniques benefit computer graphics techniques and vice versa, and cover research on analysis, manipulation, synthesis, and interaction. We also discuss existing problems and suggest possible further research directions.
