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20182025
most citedVisual Speech Recognition for Multiple Languages in the Wild

158 citations · 646 across the 34 of their papers we have counts for

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Showing 2022Show all

7 papers · 1 filter

cs.LG2022★ 13 cited

Jointly Learning Visual and Auditory Speech Representations from Raw Data

Alexandros Haliassos, Pingchuan Ma, Rodrigo Mira +2

We present RAVEn, a self-supervised multi-modal approach to jointly learn visual and auditory speech representations. Our pre-training objective involves encoding masked inputs, an…

eess.AS2022

Streaming Audio-Visual Speech Recognition with Alignment Regularization

Pingchuan Ma, Niko Moritz, Stavros Petridis +2

In this work, we propose a streaming AV-ASR system based on a hybrid connectionist temporal classification (CTC)/attention neural network architecture. The audio and the visual enc…

cs.CV2022★ 59 cited

Training Strategies for Improved Lip-reading

Pingchuan Ma, Yujiang Wang, Stavros Petridis +2

Several training strategies and temporal models have been recently proposed for isolated word lip-reading in a series of independent works. However, the potential of combining the…

cs.CV2022★ 4 cited

RISP: Rendering-Invariant State Predictor with Differentiable Simulation and Rendering for Cross-Domain Parameter Estimation

Pingchuan Ma, Tao Du, Joshua B. Tenenbaum +2

This work considers identifying parameters characterizing a physical system's dynamic motion directly from a video whose rendering configurations are inaccessible. Existing solutio…

cs.RO2022★ 4 cited

Fast Aquatic Swimmer Optimization with Differentiable Projective Dynamics and Neural Network Hydrodynamic Models

Elvis Nava, John Z. Zhang, Mike Y. Michelis +5

Aquatic locomotion is a classic fluid-structure interaction (FSI) problem of interest to biologists and engineers. Solving the fully coupled FSI equations for incompressible Navier…

cs.CV2022★ 6 cited

Self-supervised Video-centralised Transformer for Video Face Clustering

Yujiang Wang, Mingzhi Dong, Jie Shen +5

This paper presents a novel method for face clustering in videos using a video-centralised transformer. Previous works often employed contrastive learning to learn frame-level repr…