no code implementations • EMNLP 2020 • Jingyi Zhang, Josef van Genabith
In order to make use of different types of human evaluation data for supervised learning, we present a multi-task learning QE model that jointly learns two tasks: score a translation and rank two translations.
3 code implementations • 22 Apr 2024 • Xiaoning Liu, Zongwei Wu, Ao Li, Florin-Alexandru Vasluianu, Yulun Zhang, Shuhang Gu, Le Zhang, Ce Zhu, Radu Timofte, Zhi Jin, Hongjun Wu, Chenxi Wang, Haitao Ling, Yuanhao Cai, Hao Bian, Yuxin Zheng, Jing Lin, Alan Yuille, Ben Shao, Jin Guo, Tianli Liu, Mohao Wu, Yixu Feng, Shuo Hou, Haotian Lin, Yu Zhu, Peng Wu, Wei Dong, Jinqiu Sun, Yanning Zhang, Qingsen Yan, Wenbin Zou, Weipeng Yang, Yunxiang Li, Qiaomu Wei, Tian Ye, Sixiang Chen, Zhao Zhang, Suiyi Zhao, Bo wang, Yan Luo, Zhichao Zuo, Mingshen Wang, Junhu Wang, Yanyan Wei, Xiaopeng Sun, Yu Gao, Jiancheng Huang, Hongming Chen, Xiang Chen, Hui Tang, Yuanbin Chen, Yuanbo Zhou, Xinwei Dai, Xintao Qiu, Wei Deng, Qinquan Gao, Tong Tong, Mingjia Li, Jin Hu, Xinyu He, Xiaojie Guo, sabarinathan, K Uma, A Sasithradevi, B Sathya Bama, S. Mohamed Mansoor Roomi, V. Srivatsav, Jinjuan Wang, Long Sun, Qiuying Chen, Jiahong Shao, Yizhi Zhang, Marcos V. Conde, Daniel Feijoo, Juan C. Benito, Alvaro García, Jaeho Lee, Seongwan Kim, Sharif S M A, Nodirkhuja Khujaev, Roman Tsoy, Ali Murtaza, Uswah Khairuddin, Ahmad 'Athif Mohd Faudzi, Sampada Malagi, Amogh Joshi, Nikhil Akalwadi, Chaitra Desai, Ramesh Ashok Tabib, Uma Mudenagudi, Wenyi Lian, Wenjing Lian, Jagadeesh Kalyanshetti, Vijayalaxmi Ashok Aralikatti, Palani Yashaswini, Nitish Upasi, Dikshit Hegde, Ujwala Patil, Sujata C, Xingzhuo Yan, Wei Hao, Minghan Fu, Pooja Choksy, Anjali Sarvaiya, Kishor Upla, Kiran Raja, Hailong Yan, Yunkai Zhang, Baiang Li, Jingyi Zhang, Huan Zheng
This paper reviews the NTIRE 2024 low light image enhancement challenge, highlighting the proposed solutions and results.
2 code implementations • 16 Apr 2024 • Bin Ren, Nancy Mehta, Radu Timofte, Hongyuan Yu, Cheng Wan, Yuxin Hong, Bingnan Han, Zhuoyuan Wu, Yajun Zou, Yuqing Liu, Jizhe Li, Keji He, Chao Fan, Heng Zhang, Xiaolin Zhang, Xuanwu Yin, Kunlong Zuo, Bohao Liao, Peizhe Xia, Long Peng, Zhibo Du, Xin Di, Wangkai Li, Yang Wang, Wei Zhai, Renjing Pei, Jiaming Guo, Songcen Xu, Yang Cao, ZhengJun Zha, Yan Wang, Yi Liu, Qing Wang, Gang Zhang, Liou Zhang, Shijie Zhao, Long Sun, Jinshan Pan, Jiangxin Dong, Jinhui Tang, Xin Liu, Min Yan, Menghan Zhou, Yiqiang Yan, Yixuan Liu, Wensong Chan, Dehua Tang, Dong Zhou, Li Wang, Lu Tian, Barsoum Emad, Bohan Jia, Junbo Qiao, Yunshuai Zhou, Yun Zhang, Wei Li, Shaohui Lin, Shenglong Zhou, Binbin Chen, Jincheng Liao, Suiyi Zhao, Zhao Zhang, Bo wang, Yan Luo, Yanyan Wei, Feng Li, Mingshen Wang, Yawei Li, Jinhan Guan, Dehua Hu, Jiawei Yu, Qisheng Xu, Tao Sun, Long Lan, Kele Xu, Xin Lin, Jingtong Yue, Lehan Yang, Shiyi Du, Lu Qi, Chao Ren, Zeyu Han, YuHan Wang, Chaolin Chen, Haobo Li, Mingjun Zheng, Zhongbao Yang, Lianhong Song, Xingzhuo Yan, Minghan Fu, Jingyi Zhang, Baiang Li, Qi Zhu, Xiaogang Xu, Dan Guo, Chunle Guo, Jiadi Chen, Huanhuan Long, Chunjiang Duanmu, Xiaoyan Lei, Jie Liu, Weilin Jia, Weifeng Cao, Wenlong Zhang, Yanyu Mao, Ruilong Guo, Nihao Zhang, Qian Wang, Manoj Pandey, Maksym Chernozhukov, Giang Le, Shuli Cheng, Hongyuan Wang, Ziyan Wei, Qingting Tang, Liejun Wang, Yongming Li, Yanhui Guo, Hao Xu, Akram Khatami-Rizi, Ahmad Mahmoudi-Aznaveh, Chih-Chung Hsu, Chia-Ming Lee, Yi-Shiuan Chou, Amogh Joshi, Nikhil Akalwadi, Sampada Malagi, Palani Yashaswini, Chaitra Desai, Ramesh Ashok Tabib, Ujwala Patil, Uma Mudenagudi
In sub-track 1, the practical runtime performance of the submissions was evaluated, and the corresponding score was used to determine the ranking.
no code implementations • 8 Mar 2024 • Jingyi Zhang, Peng Zhang, Jingjing Wang, Di Xie, ShiLiang Pu
However, current sequence-based face forgery detection methods use general video classification networks directly, which discard the special and discriminative motion information for face manipulation detection.
1 code implementation • 25 Feb 2024 • Baiang Li, Zhao Zhang, Huan Zheng, Xiaogang Xu, Yanyan Wei, Jingyi Zhang, Jicong Fan, Meng Wang
Our RTB is used for attention selection of rain-affected and unaffected regions and local modeling of mixed scales.
no code implementations • 9 Jan 2024 • Jiaxing Huang, Kai Jiang, Jingyi Zhang, Han Qiu, Lewei Lu, Shijian Lu, Eric Xing
SAMs work with two types of prompts including spatial prompts (e. g., points) and semantic prompts (e. g., texts), which work together to prompt SAMs to segment anything on downstream datasets.
no code implementations • 27 Dec 2023 • Jiaxing Huang, Jingyi Zhang, Kai Jiang, Han Qiu, Shijian Lu
Traditional computer vision generally solves each single task independently by a dedicated model with the task instruction implicitly designed in the model architecture, arising two limitations: (1) it leads to task-specific models, which require multiple models for different tasks and restrict the potential synergies from diverse tasks; (2) it leads to a pre-defined and fixed model interface that has limited interactivity and adaptability in following user' task instructions.
no code implementations • ICCV 2023 • Jingyi Zhang, Jiaxing Huang, Xueying Jiang, Shijian Lu
However, the source predictions of target data are often noisy and training with them is prone to learning collapses.
no code implementations • 29 Jun 2023 • Jiaxing Huang, Jingyi Zhang, Han Qiu, Sheng Jin, Shijian Lu
Traditional domain adaptation assumes the same vocabulary across source and target domains, which often struggles with limited transfer flexibility and efficiency while handling target domains with different vocabularies.
1 code implementation • 20 Apr 2023 • Yusser Al Ghussin, Jingyi Zhang, Josef van Genabith
We show that document-level NMT models trained with only parallel paragraphs from Paracrawl can be used to translate real documents from TED, News and Europarl, outperforming sentence-level NMT models.
1 code implementation • 3 Apr 2023 • Jingyi Zhang, Jiaxing Huang, Sheng Jin, Shijian Lu
Most visual recognition studies rely heavily on crowd-labelled data in deep neural networks (DNNs) training, and they usually train a DNN for each single visual recognition task, leading to a laborious and time-consuming visual recognition paradigm.
no code implementations • 27 Mar 2023 • Wenhao Qiu, Sichao Fu, Jingyi Zhang, Chengxiang Lei, Qinmu Peng
And then, a text encoder is introduced to automatically generate the corresponding semantic (text) labels for each image from the base classes.
Ranked #1 on Few-Shot Class-Incremental Learning on CUB-200-2011
1 code implementation • CVPR 2023 • Lingke Kong, X. Sharon Qi, Qijin Shen, Jiacheng Wang, Jingyi Zhang, Yanle Hu, Qichao Zhou
IMSE creates an accurate multi-modal spatial evaluator to measure spatial differences between two images, and then optimizes registration by minimizing the error predicted of the evaluator.
1 code implementation • 3 Jan 2023 • Qingyi Pan, Ning Guo, Letu Qingge, Jingyi Zhang, Pei Yang
To verify the effectiveness of the proposed PMT-IQA model, we conduct experiments on four widely used public datasets, and the experimental results indicate that the performance of PMT-IQA is superior to the comparison approaches, and both MS and PMT modules improve the model's performance.
1 code implementation • 1 Jan 2023 • Fei Yin, Yong Zhang, Baoyuan Wu, Yan Feng, Jingyi Zhang, Yanbo Fan, Yujiu Yang
In the scenario of black-box adversarial attack, the target model's parameters are unknown, and the attacker aims to find a successful adversarial perturbation based on query feedback under a query budget.
no code implementations • 1 Dec 2022 • Zichen Tian, Chuhui Xue, Jingyi Zhang, Shijian Lu
We study domain adaptive scene text detection, a largely neglected yet very meaningful task that aims for optimal transfer of labelled scene text images while handling unlabelled images in various new domains.
no code implementations • 1 Sep 2022 • Junyi Liu, Yifu Tang, Haimeng Zhao, Xieheng Wang, Fangyu Li, Jingyi Zhang
In order to train a global multi-class classifier without sharing the raw data across all nodes, the main result of our study is designing a multi-node multi-class classification ensemble approach.
no code implementations • CVPR 2023 • Gongjie Zhang, Zhipeng Luo, Zichen Tian, Jingyi Zhang, Xiaoqin Zhang, Shijian Lu
Multi-scale features have been proven highly effective for object detection but often come with huge and even prohibitive extra computation costs, especially for the recent Transformer-based detectors.
2 code implementations • 9 Aug 2022 • Ruitong Zhang, Hao Peng, Yingtong Dou, Jia Wu, Qingyun Sun, Jingyi Zhang, Philip S. Yu
DBSCAN is widely used in many scientific and engineering fields because of its simplicity and practicality.
1 code implementation • 26 Jul 2022 • Cheng Ma, Jingyi Zhang, Jie zhou, Jiwen Lu
On the other hand, we propose a parallel network which includes two branches of cascaded lookup tables which process different components of the input low-resolution images.
no code implementations • CVPR 2023 • Jingyi Zhang, Jiaxing Huang, Xiaoqin Zhang, Shijian Lu
Domain adaptive panoptic segmentation aims to mitigate data annotation challenge by leveraging off-the-shelf annotated data in one or multiple related source domains.
Ranked #2 on Domain Adaptation on Panoptic SYNTHIA-to-Cityscapes
no code implementations • 31 May 2022 • Jingyi Zhang, Cheng Meng, Jun Yu, Mengrui Zhang, Wenxuan Zhong, Ping Ma
Theoretically, we show the selected subsample can be used for efficient density estimation by deriving the convergence rate for the proposed subsample kernel density estimator.
no code implementations • CVPR 2022 • Jialian Li, Jingyi Zhang, Zhiyong Wang, Siqi Shen, Chenglu Wen, Yuexin Ma, Lan Xu, Jingyi Yu, Cheng Wang
Quantitative and qualitative experiments show that our method outperforms the techniques based only on RGB images.
Ranked #3 on 3D Human Pose Estimation on SLOPER4D (using extra training data)
no code implementations • 8 Mar 2022 • Jibing Gong, Yao Wan, Ye Liu, Xuewen Li, Yi Zhao, Cheng Wang, YuTing Lin, Xiaohan Fang, Wenzheng Feng, Jingyi Zhang, Jie Tang
Despite the usefulness of this service, we consider that recommending courses to users directly may neglect their varying degrees of expertise.
no code implementations • ACL 2021 • Jingyi Zhang, Josef van Genabith
We further fine-tune the target-to-source attention in the BTBA model to obtain better alignments using a full context based optimization method and self-supervised training.
no code implementations • 13 Jul 2021 • Jingyi Zhang, Xiaoxiao Sun
The divide-and-conquer method has been widely used for estimating large-scale kernel ridge regression estimates.
no code implementations • CVPR 2022 • Jingyi Zhang, Jiaxing Huang, Zichen Tian, Shijian Lu
Second, it introduces multi-view spectral learning that learns useful unsupervised representations by maximizing mutual information among multiple ST-generated spectral views of each target sample.
1 code implementation • NeurIPS 2019 • Cheng Meng, Yuan Ke, Jingyi Zhang, Mengrui Zhang, Wenxuan Zhong, Ping Ma
We theoretically show the proposed dimension reduction method can consistently estimate the most ``informative'' projection direction in each iteration.
no code implementations • 20 May 2021 • Jingyi Zhang, Huolan Zhu, Yongkai Chen, Chenguang Yang, Huimin Cheng, Yi Li, Wenxuan Zhong, Fang Wang
Background: Extensive clinical evidence suggests that a preventive screening of coronary heart disease (CHD) at an earlier stage can greatly reduce the mortality rate.
1 code implementation • 16 Apr 2021 • Hao Peng, Ruitong Zhang, Yingtong Dou, Renyu Yang, Jingyi Zhang, Philip S. Yu
To avoid the embedding over-assimilation among different types of nodes, we employ a label-aware neural similarity measure to ascertain the most similar neighbors based on node attributes.
Ranked #3 on Node Classification on Amazon-Fraud
1 code implementation • 2 Apr 2021 • Xuelun Shen, Cheng Wang, Xin Li, Qian Hu, Jingyi Zhang
This paper presents a matching network to establish point correspondence between images.
no code implementations • CVPR 2023 • Jingyi Zhang, Jiaxing Huang, Zhipeng Luo, Gongjie Zhang, Xiaoqin Zhang, Shijian Lu
DA-DETR introduces a novel CNN-Transformer Blender (CTBlender) that fuses the CNN features and Transformer features ingeniously for effective feature alignment and knowledge transfer across domains.
1 code implementation • CVPR 2021 • Gengcong Yang, Jingyi Zhang, Yong Zhang, Baoyuan Wu, Yujiu Yang
The ambiguity naturally leads to the issue of \emph{implicit multi-label}, motivating the need for diverse predictions.
no code implementations • 24 Feb 2021 • Jingjing Wang, Jingyi Zhang, Ying Bian, Youyi Cai, Chunmao Wang, ShiLiang Pu
In this paper, we propose a self-domain adaptation framework to leverage the unlabeled test domain data at inference.
no code implementations • 9 Nov 2020 • Jingyi Zhang, Yong Zhang, Baoyuan Wu, Yanbo Fan, Fumin Shen, Heng Tao Shen
We propose to incorporate the prior about the co-occurrence of relation pairs into the graph to further help alleviate the class imbalance issue.
1 code implementation • NeurIPS 2020 • Cheng Meng, Jun Yu, Jingyi Zhang, Ping Ma, Wenxuan Zhong
The proposed method, named principal optimal transport direction (POTD), estimates the basis of the SDR subspace using the principal directions of the optimal transport coupling between the data respecting different response categories.
no code implementations • 7 Aug 2020 • Jingyi Zhang, Wenxuan Zhong, Ping Ma
Optimal transport has been one of the most exciting subjects in mathematics, starting from the 18th century.
no code implementations • ACL 2020 • Hongfei Xu, Josef van Genabith, Deyi Xiong, Qiuhui Liu, Jingyi Zhang
Considering that modeling phrases instead of words has significantly improved the Statistical Machine Translation (SMT) approach through the use of larger translation blocks ("phrases") and its reordering ability, modeling NMT at phrase level is an intuitive proposal to help the model capture long-distance relationships.
no code implementations • ACL 2020 • Hongfei Xu, Qiuhui Liu, Josef van Genabith, Deyi Xiong, Jingyi Zhang
In this paper, we first empirically demonstrate that a simple modification made in the official implementation, which changes the computation order of residual connection and layer normalization, can significantly ease the optimization of deep Transformers.
no code implementations • WS 2019 • Jingyi Zhang, Josef van Genabith
This paper describes the DFKI-NMT submission to the WMT19 News translation task.
1 code implementation • ECCV 2018 • Jingyi Zhang, Fumin Shen, Li Liu, Fan Zhu, Mengyang Yu, Ling Shao, Heng Tao Shen, Luc van Gool
The generative model learns a mapping that the distributions of sketches can be indistinguishable from the distribution of natural images using an adversarial loss, and simultaneously learns an inverse mapping based on the cycle consistency loss in order to enhance the indistinguishability.
no code implementations • SEMEVAL 2018 • Thorsten Keiper, Zhonghao Lyu, Sara Pooladzadeh, Yuan Xu, Jingyi Zhang, Anne Lauscher, Simone Paolo Ponzetto
Large repositories of scientific literature call for the development of robust methods to extract information from scholarly papers.
no code implementations • NAACL 2018 • Jingyi Zhang, Masao Utiyama, Eiichro Sumita, Graham Neubig, Satoshi Nakamura
Specifically, for an input sentence, we use a search engine to retrieve sentence pairs whose source sides are similar with the input sentence, and then collect $n$-grams that are both in the retrieved target sentences and aligned with words that match in the source sentences, which we call "translation pieces".
no code implementations • IJCNLP 2017 • Jingyi Zhang, Masao Utiyama, Eiichro Sumita, Graham Neubig, Satoshi Nakamura
Compared to traditional statistical machine translation (SMT), neural machine translation (NMT) often sacrifices adequacy for the sake of fluency.