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Nicholas Yuan

6 accepted papers

2022

Efficient Document-level Event Extraction via Pseudo-Trigger-aware Pruned Complete Graph

IJCAI 2022poster

Most previous studies of document-level event extraction mainly focus on building argument chains in an autoregressive way, which achieves a certain success but is inefficient in both training and inference. In contrast to the previous studies, we propose a fast and lightweight model named as PTPCG…

2022

Flow-Based Unconstrained Lip to Speech Generation

AAAI 2022technical

Unconstrained lip-to-speech aims to generate corresponding speeches based on silent facial videos with no restriction to head pose or vocabulary. It is desirable to generate intelligible and natural speech with a fast speed in unconstrained settings. Currently, to handle the more complicated scena…

2022

Look Closer To Supervise Better: One-Shot Font Generation via Component-Based Discriminator

CVPR 2022oral

Automatic font generation remains a challenging research issue due to the large amounts of characters with complicated structures. Typically, only a few samples can serve as the style/content reference (termed few-shot learning), which further increases the difficulty to preserve local style pattern…

Cited by 72PDFcodeScholar
2022

Parallel and High-Fidelity Text-to-Lip Generation

AAAI 2022technical

As a key component of talking face generation, lip movements generation determines the naturalness and coherence of the generated talking face video. Prior literature mainly focuses on speech-to-lip generation while there is a paucity in text-to-lip (T2L) generation. T2L is a challenging task and ex…

2022

SwinTextSpotter: Scene Text Spotting via Better Synergy Between Text Detection and Text Recognition

CVPR 2022poster

End-to-end scene text spotting has attracted great attention in recent years due to the success of excavating the intrinsic synergy of the scene text detection and recognition. However, recent state-of-the-art methods usually incorporate detection and recognition simply by sharing the backbone, whic…

Cited by 151PDFcodeScholar
2021

Denoising Distantly Supervised Named Entity Recognition via a Hypergeometric Probabilistic Model

AAAI 2021technical

Denoising is the essential step for distant supervision based named entity recognition. Previous denoising methods are mostly based on instance-level confidence statistics, which ignore the variety of the underlying noise distribution on different datasets and entity types. This makes them difficult…