Zhejiang Dahua Technology Co., Ltd.

Advanced New Technologies Co., Ltd.

Zhejiang University

Zhejiang Huaray Technology Co., Ltd.

Shejiang Dahua Technology Co., Ltd.

Advanced Nova Technologies (Singapore) Holding Pte. Ltd.

Jun Yin

Dong Jiang

Jucai Lin

Cheng Fang

Feiyang Zeng

Xingming Zhang

Jiangming Zhu

Jun Wu

Jian Wu

Liquan Fu

Wei Lu

Xue Zhang

Qiankun Li

Zhicheng Ye

Huadong Pan

Yao Chen

Yang Li

Jianzhong Fu

Huayong Yang

Yifan Wang

Hui Su

Yongtao Yang

Bingyun Lv

Xuejiao Ma

Zhangwei Zhou

Yuanqiang Yuan

Fangbo Mu

Zhuqiang Bao

Qing Guo

Libo Sun

Bingyun Lyu

Yun Xie

Qijiang Mao

Yidong Jin

Chenge Liao

Yichao Chen

Yaonong Wang

Ruidong Fang

Bangjie Tang

Chunmei Nian

The present disclosure relates to systems and methods for object recognition. The systems may obtain an image associated with an object. The systems may determine, using a recognition model, an initial recognition result of the object based on the image. The initial recognition result may include a plurality of initial recognition values corresponding to a plurality of predetermined categories respectively. Each of the plurality of initial recognition values may indicate an initial probability that the object corresponds to a corresponding predetermined category. In response to determining that the initial recognition result satisfies a preset condition, for each of the plurality of predetermined categories, the systems may obtain a reference probability corresponding to the predetermined category. The systems may determine a target recognition result of the object by adjusting the plurality of initial recognition values based on a plurality of reference probabilities corresponding to the plurality of predetermined categories respectively. The target recognition result may include a plurality of target recognition values corresponding to the plurality of predetermined categories respectively. Each of the plurality of target recognition values may indicate a target probability that the object corresponds to a corresponding predetermined category.

Systems and methods for object recognition

The present disclosure may relate to systems and methods for inter frame prediction of a video. A method may include setting, based on a block to be predicted of an image frame, a search template. The method may also include searching for, based on a search strategy, an optimal search block of the search template in a reference frame of the image frame. The method may further include determining, based on the optimal search block, prediction information of the block to be predicted.

Systems and methods for inter frame prediction of a video

A device for transferring micro-components and a method of manufacturing the device are provided. The device includes a substrate, a metal wire, and a plurality of silicon electrodes. The metal wire is formed on a flat surface of the substrate and includes a plurality of electrode driving units. The silicon electrodes are formed on a side of the metal wire opposing to the substrate. Each silicon electrode corresponds to each electrode driving unit and is driven by the electrode driving unit to pick or release each micro-component. According to the present application, the device may electrostatically adsorb a massive amount of micro-components to achieve transferring the massive amount of the micro-components, dramatically improving a transfer efficiency.

Target re-identification method, network training method thereof, and related device

The present disclosure may relate to a system and a method for video coding. The method may include determining at least one classification mode of a first component of a first pixel for a block in an image frame based on at least one pixel value of at least one second component of at least one second pixel that surrounds the first pixel. The method may also include generating a target classification result by classifying the first component based on at least a portion of the at least one classification mode. The method may also include compensating the first component based on an optimal compensation value of the target classification result.

Methods and systems for video coding

An image coding system is provided. The system may determine a coding unit in an image and divide the coding unit into a plurality of coding sub-units. For at least one coding sub-unit of the plurality of coding sub-units, the system may determine multiple reference lines of the at least one coding sub-unit. The system may determine a target prediction mode associated with one of the at least one coding sub-unit. The system may determine a predicted coding sub-unit corresponding to the one of the at least one coding sub-unit based on the target prediction mode and the multiple reference lines of the at least one coding sub-unit. The system may determine a predicted coding unit corresponding to the coding unit based at least in part on the predicted coding sub-unit.

Systems and methods for predicting coding units in images

The present disclosure relates to systems and methods for video encoding. The systems may determine a current string in a coding unit (CU) of an image frame. The current string may include one or more pixels. The systems may determine, based on a first pixel in the current string, a reference matching pixel of the first pixel by searching a searching area. The searching area may include a plurality of matching pixels The systems may determine, based on the reference matching pixel and matching patterns, a count of matching pixels in each of a plurality of groups, corresponding to the matching patterns, of the current string. The systems may further determine, based on counts of matching pixels in the plurality of groups corresponding to the matching patterns, a target prediction of the current string.

Systems and methods for string video coding

The present disclosure relates to systems and methods for image prediction in video processing. A method may include obtaining a target block that has been predicted in an image frame. The method may also include determining, from the target block, one or more target regions to be compensated. The one or more target regions may be adjacent to at least one boundary of the target block. Each of the one or more target regions may have a predictive value. The method may further include, for a target region of the one or more target regions, determining an updated predictive value of the target region based on the predictive value of the target region and pixel values of pixels in a reference region corresponding to the target region.

Systems and methods for image prediction

Systems and methods for predicting a coding block are provided. In some embodiments, the system may obtain the coding block in an image. The system may determine, based on the coding block, one or more searching templates corresponding to the coding block. For each of the one or more searching templates, the system may determine, based on the searching template, one or more candidate blocks from a reference region and determine a reference block corresponding to the searching template from the one or more candidate blocks. The reference region may include a plurality of reference pixels that are encoded. The system may determine, based at least in part on one or more reference blocks, a prediction block corresponding to the coding block.

Systems and methods for predicting a coding block

The present disclosure relates to systems and methods for inter prediction based on a Merge mode. The methods may include determining whether a current block in an image frame satisfies a division condition, and in response to determining that the current block satisfies the division condition, obtaining two sub-blocks by dividing the current block according to a division mode. The division mode may include a rectangular division. The methods may further include determine, based on the two sub-blocks, a prediction result of the current block.

Systems and method for inter prediction based on a merge mode

A linear model (LM) prediction method and a coder are disclosed. The method includes dividing a current coding block into at least two sub-blocks; for each of the sub-blocks, constructing a linear model, wherein parameters of the linear model are calculated by using pixel values of adjacent reconstructed pixels of the sub-block and adjacent reconstructed pixels of a reference sub-block of the sub-block; and predicting the sub-block by using the linear model, and obtaining a LM prediction value of the sub-block.

Linear model prediction method and coder

A method for intra-prediction is provided, including: determining at least one reference line of a current coding block, each of the at least one reference line comprising a plurality of first reference pixels; down-sampling the at least one reference line and obtaining a plurality of second reference pixels; performing matrix multiplication for the plurality of second reference pixels and obtaining a reference matrix; and obtaining a matrix-based intra-prediction block of the current coding block based on the reference matrix and the plurality of first reference pixels, the matrix-based intra-prediction block comprising a plurality of first pixels and a plurality of second pixels, a value of each of the first pixels is a value of a corresponding pixel in the reference matrix, and a value of each of the second pixels is obtained based on values of the first pixels and values of the first reference pixels.

Method and system for intra-prediction

An intra frame and inter frame joint prediction method is provided. The method includes determining at least one joint intra frame prediction mode of current coding block based on intra frame prediction mode of at least one encoded block of current frame, or determining the at least one joint intra frame prediction mode of the current coding block based on content characteristics of the current coding block, or taking at least one first specified intra frame prediction mode as the at least one joint intra frame prediction mode of current coding block; obtaining a joint intra frame prediction value of the current coding block based on the at least one joint intra frame prediction mode; and obtaining at least one intra frame and inter frame joint prediction value based on at least one candidate motion vector and the joint intra frame prediction value of the current coding block.

Method, codec device for intra frame and inter frame joint prediction

The present disclosure relates to systems and methods for video encoding. The systems may determine a current string in a coding unit (CU) of an image frame. The current string may include one or more pixels. The systems may determine a first cost based on pixels with a same pixel value in the current string. The systems may determine a second cost based on one or more strings that are located above the current string. The systems may further determine a prediction string of the current string based on the first cost and the second cost. To determine the prediction string of the current string based on the first cost and the second cost, the systems may designate the current string as the prediction string of the current string in response to that the first cost and the second cost are not determined.

Systems and methods for video processing

An affine prediction method, a computing device and a non-transitory storage medium are disclosed. The method includes obtaining a current coding block comprising a plurality of sub-blocks arranged in an array; dividing the current coding block into at least two areas, wherein each area of the at least two areas comprises two or more of the sub-blocks; setting a corresponding control point motion vector (CPMV) for one or more control points in the each area, respectively; and affine-predicting motion vectors (MVs) of the two or more of the sub-blocks in the each area, using the corresponding CPMV.

Affine predication method, computing device and non-transitory storage medium

The present disclosure may provide a method for route planning. The method may include obtaining a start location and a destination of a target vehicle. The method may also include obtaining a map of a target region including the start location and the destination. The map may include node information of each of a plurality of nodes. Further, the method may include obtaining motion status information associated with one or more vehicles other than the target vehicle in the target region. The method may further include determining a target route of the target vehicle based at least in part on the start location, the destination, the motion status information associated with the one or more vehicles, and the map.

Systems and methods for route planning on topographical map using vehicle motion

Growing community of inventors

Hangzhou, China

Jun Yin