Background Face image animation generates a synthetic human face video that harmoniously integrates the identity derived from the source image and facial motion obtained from the driving video.This technology could be...Background Face image animation generates a synthetic human face video that harmoniously integrates the identity derived from the source image and facial motion obtained from the driving video.This technology could be beneficial in multiple medical fields,such as diagnosis and privacy protection.Previous studies on face animation often relied on a single source image to generate an output video.With a significant pose difference between the source image and the driving frame,the quality of the generated video is likely to be suboptimal because the source image may not provide sufficient features for the warped feature map.Methods In this study,we propose a novel face-animation scheme based on multiple sources and perspective alignment to address these issues.We first introduce a multiple-source sampling and selection module to screen the optimal source image set from the provided driving video.We then propose an inter-frame interpolation and alignment module to further eliminate the misalignment between the selected source image and the driving frame.Conclusions The proposed method exhibits superior performance in terms of objective metrics and visual quality in large-angle animation scenes compared to other state-of-the-art face animation methods.It indicates the effectiveness of the proposed method in addressing the distortion issues in large-angle animation.展开更多
提出一种基于协同进化蚁群算法的求解QoS(Quality of Service)多播路由问题的新算法。算法中控制参数及路由选择策略根据迭代过程所处的不同阶段自适应调整。综合考虑QoS路由中所有约束条件的同时,也充分考虑各个约束自身的独立特性。...提出一种基于协同进化蚁群算法的求解QoS(Quality of Service)多播路由问题的新算法。算法中控制参数及路由选择策略根据迭代过程所处的不同阶段自适应调整。综合考虑QoS路由中所有约束条件的同时,也充分考虑各个约束自身的独立特性。仿真结果证明了算法收敛速度快,能满足实际网络服务质量的要求。展开更多
基金the Fund from Sichuan Provincial Key Laboratory of Intelligent Terminals(SCITLAB-20016).
文摘Background Face image animation generates a synthetic human face video that harmoniously integrates the identity derived from the source image and facial motion obtained from the driving video.This technology could be beneficial in multiple medical fields,such as diagnosis and privacy protection.Previous studies on face animation often relied on a single source image to generate an output video.With a significant pose difference between the source image and the driving frame,the quality of the generated video is likely to be suboptimal because the source image may not provide sufficient features for the warped feature map.Methods In this study,we propose a novel face-animation scheme based on multiple sources and perspective alignment to address these issues.We first introduce a multiple-source sampling and selection module to screen the optimal source image set from the provided driving video.We then propose an inter-frame interpolation and alignment module to further eliminate the misalignment between the selected source image and the driving frame.Conclusions The proposed method exhibits superior performance in terms of objective metrics and visual quality in large-angle animation scenes compared to other state-of-the-art face animation methods.It indicates the effectiveness of the proposed method in addressing the distortion issues in large-angle animation.
文摘提出一种基于协同进化蚁群算法的求解QoS(Quality of Service)多播路由问题的新算法。算法中控制参数及路由选择策略根据迭代过程所处的不同阶段自适应调整。综合考虑QoS路由中所有约束条件的同时,也充分考虑各个约束自身的独立特性。仿真结果证明了算法收敛速度快,能满足实际网络服务质量的要求。
