With the development of cloud-based data centers and multimedia technologies, cloud-based multimedia service systems have been paid more and more attention. Audio highlights detection plays an important role in the cl...With the development of cloud-based data centers and multimedia technologies, cloud-based multimedia service systems have been paid more and more attention. Audio highlights detection plays an important role in the cloud-based multimedia service system. In this paper, we proposed a novel highlight detection method to extract the audio highlight effects for the cloud-based multimedia service system using the unsupervised approach. In the proposed method, we first extract the audio features for each audio document. Then the spectral clustering scheme was used to decompose the audio document into several audio effects. Then, we introduce the TF-IDF method to label the highlight effect. We design some experiments to evaluate the performance of the proposed method, and the experimental results show that our method can achieve satisfying results.展开更多
Specular highlight detection and removal is a fundamental problem in computer vision and image processing.In this paper,we present an efficient endto-end deep learning model for automatically detecting and removing sp...Specular highlight detection and removal is a fundamental problem in computer vision and image processing.In this paper,we present an efficient endto-end deep learning model for automatically detecting and removing specular highlights in a single image.In particular,an encoder–decoder network is utilized to detect specular highlights,and then a novel Unet-Transformer network performs highlight removal;we append transformer modules instead of feature maps in the Unet architecture.We also introduce a highlight detection module as a mask to guide the removal task.Thus,these two networks can be jointly trained in an effective manner.Thanks to the hierarchical and global properties of the transformer mechanism,our framework is able to establish relationships between continuous self-attention layers,making it possible to directly model the mapping between the diffuse area and the specular highlight area,and reduce indeterminacy within areas containing strong specular highlight reflection.Experiments on public benchmark and real-world images demonstrate that our approach outperforms state-of-the-art methods for both highlight detection and removal tasks.展开更多
The far-zone scattered spectral density of a light wave on the scattering from a collection of particles is investigated, and the relationship between the character of the collection and the distribution of the scatte...The far-zone scattered spectral density of a light wave on the scattering from a collection of particles is investigated, and the relationship between the character of the collection and the distribution of the scattered spectral density is discussed. It is shown that both the number of particles and their locations in the collection play roles in the distribution of the far-zone scattered spectral density. This phenomenon may provide a potential method to reconstruct the structure character of a collection of particles from measurements of the far-zone scattered spectral density.展开更多
基金supported by National Development and Reform Commission Information Security Special FundNational Key Basic Reseerch Program of China (973 program) under Grant No.2007CB311203
文摘With the development of cloud-based data centers and multimedia technologies, cloud-based multimedia service systems have been paid more and more attention. Audio highlights detection plays an important role in the cloud-based multimedia service system. In this paper, we proposed a novel highlight detection method to extract the audio highlight effects for the cloud-based multimedia service system using the unsupervised approach. In the proposed method, we first extract the audio features for each audio document. Then the spectral clustering scheme was used to decompose the audio document into several audio effects. Then, we introduce the TF-IDF method to label the highlight effect. We design some experiments to evaluate the performance of the proposed method, and the experimental results show that our method can achieve satisfying results.
基金This work was partially funded by the National Natural Science Foundation of China(U21A20515,62172416,62172415,U2003109)Youth Innovation Promotion Association of the Chinese Academy of Sciences(2022131).
文摘Specular highlight detection and removal is a fundamental problem in computer vision and image processing.In this paper,we present an efficient endto-end deep learning model for automatically detecting and removing specular highlights in a single image.In particular,an encoder–decoder network is utilized to detect specular highlights,and then a novel Unet-Transformer network performs highlight removal;we append transformer modules instead of feature maps in the Unet architecture.We also introduce a highlight detection module as a mask to guide the removal task.Thus,these two networks can be jointly trained in an effective manner.Thanks to the hierarchical and global properties of the transformer mechanism,our framework is able to establish relationships between continuous self-attention layers,making it possible to directly model the mapping between the diffuse area and the specular highlight area,and reduce indeterminacy within areas containing strong specular highlight reflection.Experiments on public benchmark and real-world images demonstrate that our approach outperforms state-of-the-art methods for both highlight detection and removal tasks.
基金supported by the National Natural Science Foundation of China (Nos. 11404231, 61475105, and 11474253)the Construction Plan for Scientific Research Innovation Teams of Universities in Sichuan Province (No. 12TD008)
文摘The far-zone scattered spectral density of a light wave on the scattering from a collection of particles is investigated, and the relationship between the character of the collection and the distribution of the scattered spectral density is discussed. It is shown that both the number of particles and their locations in the collection play roles in the distribution of the far-zone scattered spectral density. This phenomenon may provide a potential method to reconstruct the structure character of a collection of particles from measurements of the far-zone scattered spectral density.
