Medical image segmentation is a fundamental and critical step in many image-guided
clinical approaches. Recent success of deep learning-based segmentation methods usually …

Artificial intelligence (AI) is evolving towards artificial general intelligence, which refers to the
ability of an AI system to perform a wide range of tasks and exhibit a level of intelligence …

Scaling text-to-speech (TTS) to large-scale, multi-speaker, and in-the-wild datasets is
important to capture the diversity in human speech such as speaker identities, prosodies …

While recent large-scale text-to-speech (TTS) models have achieved significant progress,
they still fall short in speech quality, similarity, and prosody. Considering speech intricately …

Large Language models (LLM) have demonstrated the capability to handle a variety of
generative tasks. This paper presents the UniAudio system, which, unlike prior task-specific …

This paper introduces VALL-E 2, the latest advancement in neural codec language models
that marks a milestone in zero-shot text-to-speech synthesis (TTS), achieving human parity …

Generative adversarial networks (GANs) have rapidly emerged as powerful tools for
generating realistic and diverse data across various domains, including computer vision and …

Recent advancements in generative speech models based on audio-text prompts have
enabled remarkable innovations like high-quality zero-shot text-to-speech. However …

Abstract 3D semantic occupancy prediction aims to obtain 3D fine-grained geometry and
semantics of the surrounding scene and is an important task for the robustness of vision …

In this paper we present a tensor decomposition and low-rank recovery approach
(LowRankOcc) for vision-based 3D semantic occupancy prediction. Conventional methods …