4 accepted papers
Action segmentation serves as a pivotal component in comprehending videos, encompassing the learning of a sequence of semantically consistent action units known as actoms. Conventional methodologies tend to require a significant consumption of time for both training and learning phases. This paper i…
Current 3D single object tracking approaches track the target based on a feature comparison between the target template and the search area. However, due to the common occlusion in LiDAR scans, it is non-trivial to conduct accurate feature comparisons on severe sparse and incomplete shapes. In this…
Point Cloud Sampling and Recovery (PCSR) is critical for massive real-time point cloud collection and processing since raw data usually requires large storage and computation. This paper addresses a fundamental problem in PCSR: How to downsample the dense point cloud with arbitrary scales while pres…
Recovering realistic textures from a largely down-sampled low resolution (LR) image with complicated patterns is a challenging problem in image super-resolution. This work investigates a novel multi-reference based super-resolution problem by proposing a Content Independent Multi-Reference Super-Res…