6 accepted papers
In recent years, speech diffusion models have advanced rapidly. Alongside the widely used U-Net architecture, transformer-based models such as the Diffusion Transformer (DiT) have also gained attention. However, current DiT speech models treat Mel spectrograms as general images, which overlooks the…
Speech synthesis technology has posed a serious threat to speaker verification systems. Currently, the most effective fake audio detection methods utilize pretrained models, and integrating features from various layers of pretrained model further enhances detection performance. However, most of the…
Most of existing semi-supervised learning methods heavily depend on labeled samples and always indistinguishably regard all unlabeled instances. However, unreliable samples lying around the boundary lines severely disturb training models. To address the problems, we pose a Class-credible Pseudo-labe…
Though generative adversarial networks (GANs) are prominent models to generate realistic and crisp images, they are unstable to train and suffer from the mode col-lapse/mixture. The problems of GANs come from approximating the intrinsic discontinuous distribution transform map with continuous DNNs.…
Skull registration plays a fundamental role in forensic science and is crucial for craniofacial reconstruction. The complicated topology, lack of anatomical features, and low quality reconstructed mesh make skull registration challenging. In this work, we propose an automatic skull registration meth…
In the 2nd International Unmanned Aerial Vehicle (UAV) Innovation Grand Prix (UAVGP) sponsored by Aviation Industry Corporation of China (AVIC), an autonomous barrel transportation mission was proposed for Rotary-wing UAV (RUAV) which aims at validating the feasibility of marine vertical replenishme…