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We present a learning-based method for extracting distinctive features on video objects. From the extracted features, we are able to derive dense ...
We present a learning-based method for extracting distinctive features on video objects. From the extracted features, we are able to derive dense ...
Abstract—We present a learning-based method for extracting distinctive features on video objects. From the extracted features, we are able to derive dense ...
Abstract—We present a learning-based method for extracting distinctive features on video objects. From the extracted features, we are able to derive dense ...
Dive into the research topics of 'Learning Dense Correspondences via Local and Non-local Feature Fusion'. Together they form a unique fingerprint. Sort by ...
SRFBN [3] is a newly proposed Feedback-based SR algorithm, the feedback block of SRFBN is with G projection groups sequentially with dense skip connections ...
Dec 7, 2022 · [4] proposed SRFBN which is a feedback mechanism based on dense connections. The base block, which is the deconvolutional layer that follows a ...
We present a novel fusion scheme between multiple intermediate convolutional features within convolutional neurual network (CNN) for dense correspondence ...
... This paper presents an innovative approach for temporal trajectory recovery and position change prediction of UAVs using dense matching networks [Truong et ...
Oct 13, 2021 · In the local regression network, the local feature embedding layer fuses the local features of point clouds with that of the registered mesh in.