4 accepted papers
Point cloud quality assessment (PCQA) has advanced significantly with synthetic datasets offering diverse distortion coverage for model training. However, when applied to new application scenarios, models often suffer from performance drops due to mismatched distortion characteristics between source
Recent transformer-based methods have achieved notable success in 3D human pose estimation. However, the most utilized self-attention mechanisms compute the attention matrix by performing a dot product on inter-vector features, which may overlook finer element-wise interactions. In this paper, we in…
The diversity and multi-dimensionality of point cloud make the no-reference point cloud quality assessment challenging. However, existing learning-based methods pay little attention on the distribution inconsistency of quality scores among different datasets, which would induce training bias during…
Effective emotion inference from user queries helps to give a more personified response for Voice Dialogue Applications(VDAs). The tremendous amounts of VDA users bring in diverse emotion expressions. How to achieve a high emotion inferring performance from large-scale Internet Voice Data in VDAs? T…