activity
20222024
most citedConsistentNeRF: Enhancing Neural Radiance Fields with 3D Consistency for Sparse View Synthesis

7 citations · 11 across the 6 of their papers we have counts for

collaborators

6 papers

cs.SD2024

One-pass Multiple Conformer and Foundation Speech Systems Compression and Quantization Using An All-in-one Neural Model

Zhaoqing Li, Haoning Xu, Tianzi Wang +7

We propose a novel one-pass multiple ASR systems joint compression and quantization approach using an all-in-one neural model. A single compression cycle allows multiple nested sys…

cs.CV2024

GSTalker: Real-time Audio-Driven Talking Face Generation via Deformable Gaussian Splatting

Bo Chen, Shoukang Hu, Qi Chen +4

We present GStalker, a 3D audio-driven talking face generation model with Gaussian Splatting for both fast training (40 minutes) and real-time rendering (125 FPS) with a 35 m…

cs.CV20232 cited

HumanLiff: Layer-wise 3D Human Generation with Diffusion Model

Shoukang Hu, Fangzhou Hong, Tao Hu +5

3D human generation from 2D images has achieved remarkable progress through the synergistic utilization of neural rendering and generative models. Existing 3D human generative mode…

cs.CV20237 cited

ConsistentNeRF: Enhancing Neural Radiance Fields with 3D Consistency for Sparse View Synthesis

Shoukang Hu, Kaichen Zhou, Kaiyu Li +6

Neural Radiance Fields (NeRF) has demonstrated remarkable 3D reconstruction capabilities with dense view images. However, its performance significantly deteriorates under sparse vi…

cs.CL20221 cited

Bayesian Neural Network Language Modeling for Speech Recognition

Boyang Xue, Shoukang Hu, Junhao Xu +3

State-of-the-art neural network language models (NNLMs) represented by long short term memory recurrent neural networks (LSTM-RNNs) and Transformers are becoming highly complex. Th…

eess.AS20221 cited

Neural Architecture Search For LF-MMI Trained Time Delay Neural Networks

Shoukang Hu, Xurong Xie, Mingyu Cui +6

State-of-the-art automatic speech recognition (ASR) system development is data and computation intensive. The optimal design of deep neural networks (DNNs) for these systems often…