5 accepted papers
Creating interactive digital environments for gaming, robotics, and simulation relies on articulated 3D objects whose functionality emerges from their part geometry and kinematic structure. However, existing approaches remain fundamentally limited: optimization-based reconstruction methods require s
Understanding objects at the level of their constituent parts is fundamental to advancing computer vision, graphics, and robotics. While datasets like PartNet have driven progress in 3D part understanding, their reliance on untextured geometries and expert-dependent annotation limits scalability and…
We have recently seen tremendous progress in photo-real human modeling and rendering. Yet efficiently rendering realistic human performance and integrating it into the rasterization pipeline remains challenging. In this paper we present HiFi4G an explicit and compact Gaussian-based approach for high…
Incorporating frame-level phonetic information during the extraction of speaker embeddings has been shown to enhance the performance of speaker verification systems. However, previous studies have primarily relied on phonetic information obtained from pre-trained models of monolingual automatic spee…
Deep neural network models based on x-vector have become the most popular framework for speaker recognition, and the quality of speaker features (embeddings) is important for open-set tasks such as speaker verification and speaker diarization. Currently, the most popular loss function is based on ma…