Abstract: An object rendering method includes: obtaining a parameterized model corresponding to a to-be-rendered object; based on a target viewpoint, determining multiple spatial points in a three-dimensional space corresponding to the parameterized model; for each of the multiple spatial points, for each of the multiple source viewpoints, based on position information of the spatial point, the parameterized model and the multiple original images, generating a target feature vector corresponding to the spatial point and matching the source viewpoint; and based on multiple target feature vectors corresponding to the spatial point and candidate color information of a projection point of the spatial point on each of the multiple original images, generating volume density and target color information corresponding to the spatial point; and based on volume densities and target color information respectively corresponding to the multiple spatial points, generating a rendered image of the to-be-rendered object under the targe

Abstract: Provided are a face image processing method and apparatus, an image device, and a storage medium. The face image processing method includes: acquiring first-key-point information of a first face image; performing position transformation on the first-key-point information to obtain second-key-point information conforming to a second facial geometric attribute, the second facial geometric attribute being different from a first facial geometric attribute corresponding to the first-key-point information; and performing facial texture coding processing by utilizing a neural network and the second-key-point information to obtain a second face image.

Abstract: Provided are methods and apparatuses for positioning face feature points. The method includes: carrying out edge detection on a face image to obtain a face feature line image; and fusing the face image and the face feature line image to obtain position information of face feature points.

Abstract: Methods, apparatuses, devices and computer-readable storage media for action transfer are provided. In one aspect, a method includes: obtaining an initial video involving an action sequence of an initial object, identifying a two-dimensional skeleton keypoint sequence of the initial object from plural frames of image in the initial video, converting the two-dimensional skeleton keypoint sequence of the initial object into a three-dimensional skeleton keypoint sequence of a target object, and generating a target video involving an action sequence of the target object based on the three-dimensional skeleton keypoint sequence of the target object.

Abstract: Face shape information and head posture information are extracted from each face image. Facial expression information is acquired according to an audio clip corresponding to the each face image. Face key point information of the each face image is acquired according to the facial expression information, the face shape information, and the head posture information. Face images acquired are inpainted according to the face key point information, acquiring each generated image. A target video is generated according to the each generated image.

Abstract: Provided are a face image processing method and apparatus, an image device, and a storage medium. The face image processing method includes: acquiring first-key-point information of a first face image; performing position transformation on the first-key-point information to obtain second-key-point information conforming to a second facial geometric attribute, the second facial geometric attribute being different from a first facial geometric attribute corresponding to the first-key-point information; and performing facial texture coding processing by utilizing a neural network and the second-key-point information to obtain a second face image.

Abstract: Provided are methods and apparatuses for positioning face feature points. The method includes: carrying out edge detection on a face image to obtain a face feature line image; and fusing the face image and the face feature line image to obtain position information of face feature points.

Abstract: In this invention, three genes encoding short chain neurotoxin are obtained by sea snake—Lapemis hardwickii venom gland cDNA library construction and DNA sequencing, named sn12, sn36, and sn160, respectively. The three genes are modified and amplified by PCR method, then cloned into expression vector PETTRX. The three neurotoxin genes are all highly expressed in soluble fusion protein in E. coli stain BL21-DE3 which is used as a expression host when induced with IPTG. Studies on the analgesic effects of the three recombinant short chain neurotoxins showed that three proteins, SN12, SN36 and SN160 all can significantly increase the pain threshold value of mouse.

Abstract: The present invention provides amino acid sequences obtained from the active principles in Chinese traditional medicine musk, such as SDSECPLLCEVWILK, SDSECPLLPRQGTGSLH, IDCECPLLEAKCPSFPLWPQGREEERQ, SDSECPLLLNGTNTSSRFESINCVFLSTEEGC and their acetic salts. The preparation of the amino acid sequences and their use as anti-inflammatory medicines or immunity inhibitors are also disclosed by this invention.

Abstract: In this invention, three genes encoding short chain neurotoxin are obtained by sea snake—Lapemis hardwickii venom gland cDNA library construction and DNA sequencing, named sn12, sn36, and sn160, respenctively. The three genes are modified and amplified by PCR method, then cloned into expression vector PETTRX. The three neurotoxin genes are all highly expressed in soluble fusion protein in E. coli stain BL21-DE3 which is used as a expression host when induced with IPTG. Studies on the analgesic effects of the three recombinant short chain neurotoxins showed that three proteins, SN12, SN36 and SN160 all can significantly increase the pain threshold value of mouse.