Search Results for author: Yiting Lu

Found 20 papers, 5 papers with code

On Assessing and Developing Spoken ’Grammatical Error Correction’ Systems

no code implementations NAACL (BEA) 2022 Yiting Lu, Stefano Bannò, Mark Gales

Due to a lack of end-to-end training data, SGEC is often implemented as a cascaded, modular system, consisting of speech recognition, disfluency removal, and grammatical error correction (GEC).

Grammatical Error Correction speech-recognition +1

IMAGINE-E: Image Generation Intelligence Evaluation of State-of-the-art Text-to-Image Models

no code implementations23 Jan 2025 Jiayi Lei, Renrui Zhang, Xiangfei Hu, Weifeng Lin, Zhen Li, Wenjian Sun, Ruoyi Du, Le Zhuo, Zhongyu Li, Xinyue Li, Shitian Zhao, Ziyu Guo, Yiting Lu, Peng Gao, Hongsheng Li

Beyond traditional image generation, these models exhibit capabilities across a range of fields, including controllable generation, image editing, video, audio, 3D, and motion generation, as well as computer vision tasks like semantic segmentation and depth estimation.

Depth Estimation Image Generation +3

UniMIC: Towards Universal Multi-modality Perceptual Image Compression

no code implementations6 Dec 2024 Yixin Gao, Xin Li, Xiaohan Pan, Runsen Feng, Zongyu Guo, Yiting Lu, Yulin Ren, Zhibo Chen

We present UniMIC, a universal multi-modality image compression framework, intending to unify the rate-distortion-perception (RDP) optimization for multiple image codecs simultaneously through excavating cross-modality generative priors.

Decoder Image Compression

LossAgent: Towards Any Optimization Objectives for Image Processing with LLM Agents

no code implementations5 Dec 2024 Bingchen Li, Xin Li, Yiting Lu, Zhibo Chen

We present the first loss agent, dubbed LossAgent, for low-level image processing tasks, e. g., image super-resolution and restoration, intending to achieve any customized optimization objectives of low-level image processing in different practical applications.

Image Super-Resolution Large Language Model +1

Get Large Language Models Ready to Speak: A Late-fusion Approach for Speech Generation

no code implementations27 Oct 2024 Maohao Shen, Shun Zhang, JiLong Wu, Zhiping Xiu, Ehab AlBadawy, Yiting Lu, Mike Seltzer, Qing He

Finally, we further explore MoLE-Llama in text-in-speech-out QA tasks, demonstrating its great potential as a multimodal dialog system capable of speech generation.

parameter-efficient fine-tuning Question Answering +2

Priorformer: A UGC-VQA Method with content and distortion priors

no code implementations24 Jun 2024 Yajing Pei, Shiyu Huang, Yiting Lu, Xin Li, Zhibo Chen

User Generated Content (UGC) videos are susceptible to complicated and variant degradations and contents, which prevents the existing blind video quality assessment (BVQA) models from good performance since the lack of the adapability of distortions and contents.

Video Quality Assessment Visual Question Answering (VQA)

Q-Mamba: On First Exploration of Vision Mamba for Image Quality Assessment

no code implementations13 Jun 2024 Fengbin Guan, Xin Li, Zihao Yu, Yiting Lu, Zhibo Chen

Consequently, we propose Q-Mamba by revisiting and adapting the Mamba model for three crucial IQA tasks, i. e., task-specific, universal, and transferable IQA, which reveals that the Mamba model has obvious advantages compared with existing foundational models, e. g., Swin Transformer, ViT, and CNNs, in terms of perception and computational cost for IQA.

Image Quality Assessment Mamba +1

PromptCIR: Blind Compressed Image Restoration with Prompt Learning

1 code implementation26 Apr 2024 Bingchen Li, Xin Li, Yiting Lu, Ruoyu Feng, Mengxi Guo, Shijie Zhao, Li Zhang, Zhibo Chen

Existing works on blind CIR often seek assistance from a quality factor prediction network to facilitate their network to restore compressed images.

Image Enhancement Image Restoration

NTIRE 2024 Quality Assessment of AI-Generated Content Challenge

no code implementations25 Apr 2024 Xiaohong Liu, Xiongkuo Min, Guangtao Zhai, Chunyi Li, Tengchuan Kou, Wei Sun, HaoNing Wu, Yixuan Gao, Yuqin Cao, ZiCheng Zhang, Xiele Wu, Radu Timofte, Fei Peng, Huiyuan Fu, Anlong Ming, Chuanming Wang, Huadong Ma, Shuai He, Zifei Dou, Shu Chen, Huacong Zhang, Haiyi Xie, Chengwei Wang, Baoying Chen, Jishen Zeng, Jianquan Yang, Weigang Wang, Xi Fang, Xiaoxin Lv, Jun Yan, Tianwu Zhi, Yabin Zhang, Yaohui Li, Yang Li, Jingwen Xu, Jianzhao Liu, Yiting Liao, Junlin Li, Zihao Yu, Yiting Lu, Xin Li, Hossein Motamednia, S. Farhad Hosseini-Benvidi, Fengbin Guan, Ahmad Mahmoudi-Aznaveh, Azadeh Mansouri, Ganzorig Gankhuyag, Kihwan Yoon, Yifang Xu, Haotian Fan, Fangyuan Kong, Shiling Zhao, Weifeng Dong, Haibing Yin, Li Zhu, Zhiling Wang, Bingchen Huang, Avinab Saha, Sandeep Mishra, Shashank Gupta, Rajesh Sureddi, Oindrila Saha, Luigi Celona, Simone Bianco, Paolo Napoletano, Raimondo Schettini, Junfeng Yang, Jing Fu, Wei zhang, Wenzhi Cao, Limei Liu, Han Peng, Weijun Yuan, Zhan Li, Yihang Cheng, Yifan Deng, Haohui Li, Bowen Qu, Yao Li, Shuqing Luo, Shunzhou Wang, Wei Gao, Zihao Lu, Marcos V. Conde, Xinrui Wang, Zhibo Chen, Ruling Liao, Yan Ye, Qiulin Wang, Bing Li, Zhaokun Zhou, Miao Geng, Rui Chen, Xin Tao, Xiaoyu Liang, Shangkun Sun, Xingyuan Ma, Jiaze Li, Mengduo Yang, Haoran Xu, Jie zhou, Shiding Zhu, Bohan Yu, Pengfei Chen, Xinrui Xu, Jiabin Shen, Zhichao Duan, Erfan Asadi, Jiahe Liu, Qi Yan, Youran Qu, Xiaohui Zeng, Lele Wang, Renjie Liao

A total of 196 participants have registered in the video track.

Image Quality Assessment Image Restoration +2

KVQ: Kwai Video Quality Assessment for Short-form Videos

1 code implementation CVPR 2024 Yiting Lu, Xin Li, Yajing Pei, Kun Yuan, Qizhi Xie, Yunpeng Qu, Ming Sun, Chao Zhou, Zhibo Chen

Short-form UGC video platforms, like Kwai and TikTok, have been an emerging and irreplaceable mainstream media form, thriving on user-friendly engagement, and kaleidoscope creation, etc.

Video Quality Assessment Visual Question Answering (VQA)

FreqAlign: Excavating Perception-oriented Transferability for Blind Image Quality Assessment from A Frequency Perspective

no code implementations29 Sep 2023 Xin Li, Yiting Lu, Zhibo Chen

Based on this, we propose to improve the perception-oriented transferability of BIQA by performing feature frequency decomposition and selecting the frequency components that contained the most transferable perception knowledge for alignment.

Blind Image Quality Assessment Unsupervised Domain Adaptation

HST: Hierarchical Swin Transformer for Compressed Image Super-resolution

3 code implementations21 Aug 2022 Bingchen Li, Xin Li, Yiting Lu, Sen Liu, Ruoyu Feng, Zhibo Chen

Compressed Image Super-resolution has achieved great attention in recent years, where images are degraded with compression artifacts and low-resolution artifacts.

Compressed Image Super-resolution Image Super-Resolution

StyleAM: Perception-Oriented Unsupervised Domain Adaption for Non-reference Image Quality Assessment

no code implementations29 Jul 2022 Yiting Lu, Xin Li, Jianzhao Liu, Zhibo Chen

Specifically, we find a more compact and reliable space i. e., feature style space for perception-oriented UDA based on an interesting/amazing observation, that the feature style (i. e., the mean and variance) of the deep layer in DNNs is exactly associated with the quality score in NR-IQA.

Image Quality Assessment NR-IQA +1

RTN: Reinforced Transformer Network for Coronary CT Angiography Vessel-level Image Quality Assessment

no code implementations13 Jul 2022 Yiting Lu, Jun Fu, Xin Li, Wei Zhou, Sen Liu, Xinxin Zhang, Congfu Jia, Ying Liu, Zhibo Chen

Therefore, we propose a Progressive Reinforcement learning based Instance Discarding module (termed as PRID) to progressively remove quality-irrelevant/negative instances for CCTA VIQA.

Image Quality Assessment Multiple Instance Learning

Attention Forcing for Machine Translation

1 code implementation2 Apr 2021 Qingyun Dou, Yiting Lu, Potsawee Manakul, Xixin Wu, Mark J. F. Gales

This approach guides the model with the generated output history and reference attention, and can reduce the training-inference mismatch without a schedule or a classifier.

Machine Translation NMT +2

Attention Forcing for Sequence-to-sequence Model Training

no code implementations26 Sep 2019 Qingyun Dou, Yiting Lu, Joshua Efiong, Mark J. F. Gales

This paper introduces attention forcing, which guides the model with generated output history and reference attention.

Machine Translation model +3

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