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公开(公告)号：US20240296308A1
公开(公告)日：2024-09-05
申请号：US18646852
申请日：2024-04-26
Applicant: SHANGHAITECH UNIVERSITY
Inventor： Yueyang ZHENG , Chaolin RAO , Minye WU , Xin LOU , Pingqiang ZHOU , Jingyi YU
IPC: G06N3/04
CPC classification number: G06N3/04
Abstract: A computing system for encoding a machine learning model comprises a plurality of layers and a plurality of computation units. A first set of computation units are configured to process data at a first bit width. A second set of computation units are configured to process at a second bit width. The first bit width is higher than the second bit width. A memory is coupled to the computation units. A controller is coupled to the computation units and the memory. The controller is configured to provide instructions for encoding the machine learning model. The first set of computation units are configured to compute a first set of layers and the second set of computation units are configured to compute a second set of layers.
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公开(公告)号：US20240013479A1
公开(公告)日：2024-01-11
申请号：US18369904
申请日：2023-09-19
Applicant: SHANGHAITECH UNIVERSITY
Inventor： Minye WU , Chaolin RAO , Xin LOU , Pingqiang ZHOU , Jingyi YU
CPC classification number: G06T15/55 , G06T15/20 , G06T17/20 , G06T2210/56
Abstract: A computer-implemented method includes encoding a radiance field of an object onto a machine learning model; conducting, based on a set of training images of the object, a training process on the machine learning model to obtain a trained machine learning model, wherein the training process includes a first training process using a plurality of first test sample points followed by a second training process using a plurality of second test sample points located within a threshold distance from a surface region of the object; obtaining target view parameters indicating a view direction of the object; obtaining a plurality of rays associated with a target image of the object; obtaining render sample points on the plurality of rays associated with the target image; and rendering, by inputting the render sample points to the trained machine learning model, colors associated with the pixels of the target image.
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公开(公告)号：US20210042898A1
公开(公告)日：2021-02-11
申请号：US17072397
申请日：2020-10-16
Applicant: SHANGHAITECH UNIVERSITY
Abstract: A method of image processing for occlusion removal in images and videos captured by light field camera systems. The method comprises: capturing a plurality of camera views using a plurality of cameras; capturing a plurality of depth maps using a plurality of depth sensors; generating a depth map for each camera view; calculating a target view on a focal plane corresponding to a virtual camera; set a weighting function on the pixels on the camera views based on the depth map and a virtual distance; and blending the pixels in accordance with the weighting function to generate a refocused target view.
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公开(公告)号：US20240104822A1
公开(公告)日：2024-03-28
申请号：US18531755
申请日：2023-12-07
Applicant: SHANGHAITECH UNIVERSITY
Inventor： Chaolin RAO , Minye WU , Xin LOU , Pingqiang ZHOU , Jingyi YU
CPC classification number: G06T15/005 , G06T7/90 , G06T2207/20084
Abstract: An image rendering system comprising a preprocessing unit coupled to a feature extract unit and a color rendering unit over a data bus. The preprocessing unit generates vector representations of spatial coordinates of sample points along camera rays corresponding to pixels of an image to be rendered. The feature extract unit generates a feature map of the image based on the vector representations, color and intensity values of the sample point through a first machine learning model. The color rendering unit renders the image based on the feature map through a second machine learning model. The first machine learning model is different from the second machine learning model.
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公开(公告)号：US20230360372A1
公开(公告)日：2023-11-09
申请号：US18223575
申请日：2023-07-19
Applicant: SHANGHAITECH UNIVERSITY
Inventor： Fuqiang ZHAO , Minye WU , Lan XU , Jingyi YU
CPC classification number: G06V10/774 , G06V10/82 , G06T7/50 , G06T7/80 , G06V10/761 , G06V20/64 , G06T2207/20081 , G06T2207/20084 , G06T2207/10028 , G06V40/172
Abstract: Systems, methods, and non-transitory computer-readable media are configured to obtain a set of content items to train a neural radiance field-based (NeRF-based) machine learning model for object recognition. Depth maps of objects depicted in the set of content items can be determined. A first set of training data comprising reconstructed content items depicting only the objects can be generated based on the depth maps. A second set of training data comprising one or more optimal training paths associated with the set of content items can be generated based on the depth maps. The one or more optimal training paths are generated based at least in part on a dissimilarity matrix associated with the set of content items. The NeRF-based machine learning model can be trained based on the first set of training data and the second set of training data.
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Patent Agency Ranking
公开(公告)号：US20230027234A1
公开(公告)日：2023-01-26
申请号：US17951405
申请日：2022-09-23
Applicant: Shanghaitech University
Abstract: An image-based method of modeling and rendering a three-dimensional model of an object is provided. The method comprises: obtaining a three-dimensional point cloud at each frame of a synchronized, multi-view video of an object, wherein the video comprises a plurality of frames; extracting a feature descriptor for each point in the point cloud for the plurality of frames without storing the feature descriptor for each frame; producing a two-dimensional feature map for a target camera; and using an anti-aliased convolutional neural network to decode the feature map into an image and a foreground mask.
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公开(公告)号：US20240281256A1
公开(公告)日：2024-08-22
申请号：US18646818
申请日：2024-04-26
Applicant: SHANGHAITECH UNIVERSITY
Inventor： Yuhan GU , Chaolin RAO , Minye WU , Xin LOU , Pingqiang ZHOU , Jingyi YU
CPC classification number: G06F9/3885 , G06T1/20 , G06T15/005
Abstract: A computing core for rendering an image computing core comprises a position encoding logic and a plurality of pipeline logics connected in series in a pipeline. The position encoding logic is configured to transform coordinates and directions of sampling points corresponding to a portion of the image into high dimensional representations. The plurality of pipeline logics are configured to output, based on the high dimensional representation of the coordinates and the high dimensional representation of the directions, intensity and color values of pixels corresponding to the portion of the image in one pipeline cycle. The plurality of pipeline logics are configured to run in parallel.
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公开(公告)号：US20240161388A1
公开(公告)日：2024-05-16
申请号：US18281966
申请日：2021-04-13
Applicant: SHANGHAITECH UNIVERSITY
Inventor： Haimin LUO , Minye WU , Lan XU , Jingyi YU
CPC classification number: G06T15/20 , G06T7/596 , G06T7/62 , G06T17/00 , G06T2200/04 , G06T2207/20081 , G06T2207/20084
Abstract: A deep neural network based hair rendering system is presented to model high frequency component of furry objects. Compared with existing approaches, the present method can generate photo-realistic rendering results. An acceleration method is applied in our framework, which can speed up training and rendering processes. In addition, a patch-based training scheme is introduced, which significantly increases the quality of outputs and preserves high frequency details.
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公开(公告)号：US20210082096A1
公开(公告)日：2021-03-18
申请号：US17074123
申请日：2020-10-19
Applicant: SHANGHAITECH UNIVERSITY
Abstract: A method of processing light field images for separating a transmitted layer from a reflection layer. The method comprises capturing a plurality of views at a plurality of viewpoints with different polarization angles; obtaining an initial disparity estimation for a first view using SIFT-flow, and warping the first view to a reference view; optimizing an objective function comprising a transmitted layer and a secondary layer using an Augmented Lagrange Multiplier (ALM) with Alternating Direction Minimizing (ADM) strategy; updating the disparity estimation for the first view; repeating the steps of optimizing the objective function and updating the disparity estimation until the change in the objective function between two consecutive iterations is below a threshold; and separating the transmitted layer and the secondary layer using the disparity estimation for the first view.
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公开(公告)号：US20200302155A1
公开(公告)日：2020-09-24
申请号：US16894032
申请日：2020-06-05
Applicant: SHANGHAITECH UNIVERSITY
Inventor： Zhiru SHI , Minye WU , Wengguang MA , Jingyi YU
IPC: G06K9/00 , H04N13/282 , H04N5/225
Abstract: A method of detecting and recognizing faces using a light field camera array is provided. The method includes capturing multi-view color images using the light field camera array; obtaining a depth map; conducting light field rendering using a weight function comprising a depth component and a sematic component, where the weight function assigns a ray in the light field with a weight; and detecting and recognizing a face.
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