2 citations · 5 across the 5 of their papers we have counts for
5 papers
Efficient-3DiM: Learning a Generalizable Single-image Novel-view Synthesizer in One Day
Yifan Jiang, Hao Tang, Jen-Hao Rick Chang +3
The task of novel view synthesis aims to generate unseen perspectives of an object or scene from a limited set of input images. Nevertheless, synthesizing novel views from a single…
Corpus Synthesis for Zero-shot ASR domain Adaptation using Large Language Models
Hsuan Su, Ting-Yao Hu, Hema Swetha Koppula +5
While Automatic Speech Recognition (ASR) systems are widely used in many real-world applications, they often do not generalize well to new domains and need to be finetuned on data…
Pointersect: Neural Rendering with Cloud-Ray Intersection
Jen-Hao Rick Chang, Wei-Yu Chen, Anurag Ranjan +2
We propose a novel method that renders point clouds as if they are surfaces. The proposed method is differentiable and requires no scene-specific optimization. This unique capabili…
FaceLit: Neural 3D Relightable Faces
Anurag Ranjan, Kwang Moo Yi, Jen-Hao Rick Chang +1
We propose a generative framework, FaceLit, capable of generating a 3D face that can be rendered at various user-defined lighting conditions and views, learned purely from 2D image…
Text is All You Need: Personalizing ASR Models using Controllable Speech Synthesis
Karren Yang, Ting-Yao Hu, Jen-Hao Rick Chang +2
Adapting generic speech recognition models to specific individuals is a challenging problem due to the scarcity of personalized data. Recent works have proposed boosting the amount…