Tsinghua University

Central Iron & Steel Research Institute Ministry Metallurgical Industry

Jinzhi Zhang

Lu Fang

Guangyu Wang

Haiyang Ying

Zequn Chen

Ruofan Tang

Haozhe Lin

In a method for generating a multi-dimensional scene graph with a complex light field, entity features of entities are obtained by inputting respective 2-Dimensional (2D) images captured in multiple view directions into an object detection model, and features of a respective single-view-direction scene graph are obtained by predicting a semantic relation among the entities contained in a corresponding 2D image captured in each view direction. An entity correlation for an entity among the multiple view directions is determined as an entity re-identification result. A multi-dimensional bounding box for the entity is established based on the entity re-identification result and a geometric constraint of camera parameters. A feature fusion result is obtained by fusing features of respective single-view-direction scene graphs in the multiple view directions. The multi-dimensional scene graph with the complex light field is established.

Method, system and apparatus for generating multi-dimensional scene graph with complex light field

A method includes: acquiring a semantic primitive set of a multi-view image set; acquiring a coordinate offset by inputting coordinate information and a feature vector corresponding to a first grid sampling point of the semantic primitive set into a first network model, and acquiring a second grid of the semantic primitive set based on the coordinate offset and geometric attribute information of the semantic primitive set; acquiring first feature information of a second grid sampling point by inputting coordinate information and a feature vector corresponding to the second grid sampling point, and an observation angle value into a second network model, and acquiring second feature information of the semantic primitive set based on the first feature information; and acquiring a light field reconstruction result of the multi-view image set based on an observation angle value of the semantic primitive set and third feature information extracted from the second feature information.

Method and system for semantic-driven intelligent reconstruction of large-scene sparse light field

A method and a device for gigapixel-level light field intelligent reconstruction of a large-scale scene are provided. The method includes: obtaining a coarse three-dimensional geometric model based on a multi-view three-dimensional reconstruction system; constructing an implicit representation of the meta-deformed manifold on the coarse three-dimensional geometric model; and optimizing the implicit representation of the meta-deformed manifold to obtain the light field reconstruction in the form of free viewpoint rendering of the large-scale scene.

Method and device for gigapixel-level light field intelligent reconstruction of large-scale scene

A method for large scene elastic semantic representation and self-supervised light field reconstruction is provided. The method includes acquiring a first depth map set corresponding to a target scene, in which the first depth map set includes a first depth map corresponding to at least one 5 angle of view; inputting the first depth map set into a target elastic semantic reconstruction model to obtain a second depth map set, in which the second depth map set includes a second depth map corresponding to the at least one angle of view; and fusing the second depth map corresponding to the at least one angle of view to obtain a target scene point cloud corresponding to the target scene.

Method for large scene elastic semantic representation and self-supervised light field reconstruction

A method to measure strip shape in rolling and a method of using the measuring method to control the same are provided in present invention, which can dramatically simplify the computation during the measurement of strip shape. On the basis of a prior mathematical model, the invention is realized by applying a strip rigidity coefficient q reflecting the features of a piece to be rolled, and a shape rigidity coefficient m reflecting those of a mill, to express heredity coefficient .eta..

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Beijing, China

Jinzhi Zhang