10 accepted papers
Realistic talking-head video generation is critical for virtual avatars, film production, and interactive systems. Current methods struggle with nuanced emotional expressions due to the lack of fine-grained emotion control. To address this issue, we introduce a novel two-stage method (AUHead) to dis…
Multi-view image compression (MIC) aims to achieve high compression efficiency by exploiting inter-image correlations, playing a crucial role in 3D applications. As a subfield of MIC, distributed multi-view image compression (DMIC) offers performance comparable to MIC while eliminating the need for
Generative Error Correction (GEC) has emerged as a powerful post-processing method to boost the performance of Automatic Speech Recognition (ASR) systems. In this paper, we first show that GEC models struggle to generalize beyond the specific types of errors encountered during training, limiting the…
Recent advances in text-driven motion generation have shown notable advancements. However, these works are typically limited to standardized skeletons and rely on a cumbersome retargeting process to adapt to varying skeletal configurations of diverse characters. In this paper, we present OmniSkel, a…
End-to-end speech translation (ST) for conversation recordings involves several under-explored challenges such as speaker diarization (SD) without accurate word time stamps and handling of overlapping speech in a streaming fashion. In this work, we propose DiariST, the first streaming ST and SD solu…
The growing need for instant spoken language transcription and translation is driven by increased global communication and cross-lingual interactions. This has made offering translations in multiple languages essential for user applications. Traditional approaches to automatic speech recognition (AS…
Neural transducer is now the most popular end-to-end model for speech recognition, due to its naturally streaming ability. However, it is challenging to adapt it with text-only data. Factorized neural transducer (FNT) model was proposed to mitigate this problem. The improved adaptation ability of FN…
The development of detection methods for oriented object detection remains a challenging task. A considerable obstacle is the wide variation in the shape (e.g., aspect ratio) of objects. Sample selection in general object detection has been widely studied as it plays a crucial role in the performanc…
A novel application system is proposed in this paper to achieve the generation of 3D character animation driven by markerless human body motion capture. The whole pipeline of the system consists of four parts: capturing motion data by multiple cameras, detecting 2D human body joints and estimating 3…
To develop speaker adaptation algorithms for deep neural network (DNN) that are suitable for large-scale online deployment, it is desirable that the adaptation model be represented in a compact form and learned in an unsupervised fashion. In this paper, we propose a novel low-footprint adaptation te…