In recent years,the concept of digital human has attracted widespread attention from all walks of life,and the modelling of high-fidelity human bodies,heads,and hands has been intensively studied.This paper focuses on...In recent years,the concept of digital human has attracted widespread attention from all walks of life,and the modelling of high-fidelity human bodies,heads,and hands has been intensively studied.This paper focuses on head modelling and proposes a generic head parametric model based on neural radiance fields.Specifically,we first use face recognition networks and 3D facial expression database FaceWarehouse to parameterize identity and expression semantics,respectively,and use both as conditional inputs to build a neural radiance field for the human head,thereby improving the head model’s representation ability while ensuring editing capabilities for the identity and expression of the rendered results;then,through a combination of volume rendering and neural rendering,the 3D representation of the head is rapidly rendered into the 2D plane,producing a high-fidelity image of the human head.Thanks to the well-designed loss functions and good implicit representation of the neural radiance field,our model can not only edit the identity and expression independently,but also freely modify the virtual camera position of the rendering results.It has excellent multi-view consistency,and has many applications in novel view synthesis,pose driving and more.展开更多
The assembly of a protein complex is very important for its biological function,which can be investigated by determining the order of assembly/disassembly of its protein subunits.Although static structures of many pro...The assembly of a protein complex is very important for its biological function,which can be investigated by determining the order of assembly/disassembly of its protein subunits.Although static structures of many protein com-plexes are available in the protein data bank,their assembly/disassembly orders of subunits are largely unknown.In addition to experimental techniques for studying subcomplexes in the assembly/disassembly of a protein complex,computational methods can be used to predict the assembly/disassembly order.Since sampling is a nontrivial issue in simulating the assembly/disassembly process,coarse-grained simulations are more efficient than atomic simulations are.In this work,we developed computational protocols for predicting the assembly/disassembly orders of protein complexes via coarse-grained simulations.The protocols were illustrated via two protein complexes,and the predicted assembly/disassembly orders were consistent with the available experimental data.展开更多
文摘In recent years,the concept of digital human has attracted widespread attention from all walks of life,and the modelling of high-fidelity human bodies,heads,and hands has been intensively studied.This paper focuses on head modelling and proposes a generic head parametric model based on neural radiance fields.Specifically,we first use face recognition networks and 3D facial expression database FaceWarehouse to parameterize identity and expression semantics,respectively,and use both as conditional inputs to build a neural radiance field for the human head,thereby improving the head model’s representation ability while ensuring editing capabilities for the identity and expression of the rendered results;then,through a combination of volume rendering and neural rendering,the 3D representation of the head is rapidly rendered into the 2D plane,producing a high-fidelity image of the human head.Thanks to the well-designed loss functions and good implicit representation of the neural radiance field,our model can not only edit the identity and expression independently,but also freely modify the virtual camera position of the rendering results.It has excellent multi-view consistency,and has many applications in novel view synthesis,pose driving and more.
基金supported by the National Natural Science Foundation of China(72071187,11671374,71731010,71921001)Fundamental Research Funds for the Central Universities(WK3470000017,WK2040000027)。
基金This work was supported by the National Key Research and Development Program of China(2021YFA1301504)the Chinese Academy of Sciences Strategic Priority Research Program(XDB37040202)the National Natural Science Foundation of China(91953101).
文摘The assembly of a protein complex is very important for its biological function,which can be investigated by determining the order of assembly/disassembly of its protein subunits.Although static structures of many protein com-plexes are available in the protein data bank,their assembly/disassembly orders of subunits are largely unknown.In addition to experimental techniques for studying subcomplexes in the assembly/disassembly of a protein complex,computational methods can be used to predict the assembly/disassembly order.Since sampling is a nontrivial issue in simulating the assembly/disassembly process,coarse-grained simulations are more efficient than atomic simulations are.In this work,we developed computational protocols for predicting the assembly/disassembly orders of protein complexes via coarse-grained simulations.The protocols were illustrated via two protein complexes,and the predicted assembly/disassembly orders were consistent with the available experimental data.
