Search Results for author: Tong Zheng

Found 9 papers, 5 papers with code

Incorporating Probing Signals into Multimodal Machine Translation via Visual Question-Answering Pairs

1 code implementation26 Oct 2023 Yuxin Zuo, Bei Li, Chuanhao Lv, Tong Zheng, Tong Xiao, Jingbo Zhu

This paper presents an in-depth study of multimodal machine translation (MMT), examining the prevailing understanding that MMT systems exhibit decreased sensitivity to visual information when text inputs are complete.

Attribute Multimodal Machine Translation +2

PartialFormer: Modeling Part Instead of Whole

1 code implementation23 Oct 2023 Tong Zheng, Bei Li, Huiwen Bao, Weiqiao Shan, Tong Xiao, Jingbo Zhu

The design choices in Transformer feed-forward neural networks have resulted in significant computational and parameter overhead.

Abstractive Text Summarization Machine Translation +1

EIT: Enhanced Interactive Transformer

1 code implementation20 Dec 2022 Tong Zheng, Bei Li, Huiwen Bao, Tong Xiao, Jingbo Zhu

In this paper, we propose a novel architecture, the Enhanced Interactive Transformer (EIT), to address the issue of head degradation in self-attention mechanisms.

Abstractive Text Summarization Language Modelling +2

Learning Multiscale Transformer Models for Sequence Generation

1 code implementation19 Jun 2022 Bei Li, Tong Zheng, Yi Jing, Chengbo Jiao, Tong Xiao, Jingbo Zhu

In this work, we define those scales in different linguistic units, including sub-words, words and phrases.

Multi-modality super-resolution loss for GAN-based super-resolution of clinical CT images using micro CT image database

no code implementations30 Dec 2019 Tong Zheng, Hirohisa ODA, Takayasu MORIYA, Shota NAKAMURA, Masahiro Oda, Masaki MORI, Horitsugu Takabatake, Hiroshi NATORI, Kensaku MORI

This paper newly introduces multi-modality loss function for GAN-based super-resolution that can maintain image structure and intensity on unpaired training dataset of clinical CT and micro CT volumes.

Computed Tomography (CT) Super-Resolution +1

DeepIlluminance: Contextual Illuminance Estimation via Deep Neural Networks

1 code implementation12 May 2019 Jun Zhang, Tong Zheng, Shengping Zhang, Meng Wang

First, the contextual net with a center-surround architecture extracts local contextual features from image patches, and generates initial illuminant estimates and the corresponding color corrected patches.

Color Constancy

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