TIP Volume 29 | 2020

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February, 2020

TIP Volume 29 | 2020

We present a method to compress geometry information of point clouds that explores redundancies across consecutive frames of a sequence. It uses octrees and works by progressively increasing the resolution of the octree. At each branch of the tree, we generate an approximation of the child nodes by a number of methods which are used as contexts to drive an arithmetic coder.

Image semantic segmentation tasks and methods based on weakly supervised conditions have been proposed and achieve better and better performance in recent years. However, the purpose of these tasks is mainly to simplify the labeling work. In this paper, we establish a new and more challenging task condition.

The inverse synthetic aperture radar (ISAR) imaging technique of a moving target with sparse sampling data has attracted wide attention due to its ability to reduce the data collection burden. However, traditional low-rank or 2D compressive sensing (CS)-based ISAR imaging methods can handle the random sampling or the separable sampling data only. 

Collective activity recognition, which tells what activity a group of people is performing, is a cutting-edge research topic in computer vision. Different from action performed by individuals, collective activity needs to consider the complex interactions among different people. However, most previous works require exhaustive annotations such as accurate label information of individual actions, pairwise interactions, and poses, which could not be easily available in practice. 

The prevailing characteristics of micro-videos result in the less descriptive power of each modality. The micro-video representations, several pioneer efforts proposed, are limited in implicitly exploring the consistency between different modality information but ignore the complementarity.

The prevailing characteristics of micro-videos result in the less descriptive power of each modality. The micro-video representations, several pioneer efforts proposed, are limited in implicitly exploring the consistency between different modality information but ignore the complementarity.

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