no code implementations • Findings (ACL) 2022 • Yuxia Wang, Minghan Wang, Yimeng Chen, Shimin Tao, Jiaxin Guo, Chang Su, Min Zhang, Hao Yang
Natural Language Inference (NLI) datasets contain examples with highly ambiguous labels due to its subjectivity.
no code implementations • WAT 2022 • Yilun Liu, Zhen Zhang, Shimin Tao, Junhui Li, Hao Yang
In this paper we describe our submission to the shared tasks of the 9th Workshop on Asian Translation (WAT 2022) on NICT–SAP under the team name ”HwTscSU”.
no code implementations • CCL 2022 • Zekun Deng, Hao Yang, Jun Wang
"《史记》和《汉书》具有经久不衰的研究价值。尽管两书异同的研究已经较为丰富, 但研究的全面性、完备性、科学性、客观性均仍显不足。在数字人文的视角下, 本文利用计算语言学方法, 通过对字、词、命名实体、段落等的多粒度、多角度分析, 开展对于《史》《汉》的比较研究。首先, 本文对于《史》《汉》中的字、词、命名实体的分布和特点进行对比, 以遍历穷举的考察方式提炼出两书在主要内容上的相同点与不同点, 揭示了汉武帝之前和汉武帝到西汉灭亡两段历史时期在政治、文化、思想上的重要变革与承袭。其次, 本文使用一种融入命名实体作为外部特征的文本相似度算法对于《史记》《汉书》的异文进行自动发现, 成功识别出过去研究者通过人工手段没有发现的袭用段落, 使得我们对于《史》《汉》的承袭关系形成更加完整和立体的认识。再次, 本文通过计算异文段落之间的最长公共子序列来自动得出两段异文之间存在的差异, 从宏观统计上证明了《汉书》文字风格《史记》的差别, 并从微观上进一步对二者语言特点进行了阐释, 为理解《史》《汉》异文特点提供了新的角度和启发。本研究站在数字人文的视域下, 利用先进的计算方法对于传世千年的中国古代经典进行了再审视、再发现, 其方法对于今人研究古籍有一定的借鉴价值。”
no code implementations • IWSLT (ACL) 2022 • Minghan Wang, Jiaxin Guo, Xiaosong Qiao, Yuxia Wang, Daimeng Wei, Chang Su, Yimeng Chen, Min Zhang, Shimin Tao, Hao Yang, Ying Qin
For machine translation part, we pretrained three translation models on WMT21 dataset and fine-tuned them on in-domain corpora.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
no code implementations • IWSLT (ACL) 2022 • Minghan Wang, Jiaxin Guo, Yinglu Li, Xiaosong Qiao, Yuxia Wang, Zongyao Li, Chang Su, Yimeng Chen, Min Zhang, Shimin Tao, Hao Yang, Ying Qin
The cascade system is composed of a chunking-based streaming ASR model and the SimulMT model used in the T2T track.
no code implementations • IWSLT (ACL) 2022 • Jiaxin Guo, Yinglu Li, Minghan Wang, Xiaosong Qiao, Yuxia Wang, Hengchao Shang, Chang Su, Yimeng Chen, Min Zhang, Shimin Tao, Hao Yang, Ying Qin
The paper presents the HW-TSC’s pipeline and results of Offline Speech to Speech Translation for IWSLT 2022.
no code implementations • IWSLT (ACL) 2022 • Zongyao Li, Jiaxin Guo, Daimeng Wei, Hengchao Shang, Minghan Wang, Ting Zhu, Zhanglin Wu, Zhengzhe Yu, Xiaoyu Chen, Lizhi Lei, Hao Yang, Ying Qin
This paper presents our submissions to the IWSLT 2022 Isometric Spoken Language Translation task.
no code implementations • SemEval (NAACL) 2022 • Xiaosong Qiao, Yinglu Li, Min Zhang, Minghan Wang, Hao Yang, Shimin Tao, Qin Ying
This paper describes the system for the identifying Plausible Clarifications of Implicit and Underspecified Phrases.
no code implementations • EAMT 2020 • Minghan Wang, Hao Yang, Ying Qin, Shiliang Sun, Yao Deng
We propose a unified multilingual model for humor detection which can be trained under a transfer learning framework.
no code implementations • EAMT 2020 • Hao Yang, Minghan Wang, Ning Xie, Ying Qin, Yao Deng
Compared with the commonly used NuQE baseline, BAL-QE achieves 47% (En-Ru) and 75% (En-De) of performance promotions.
no code implementations • AACL (WAT) 2020 • Zhengzhe Yu, Zhanglin Wu, Xiaoyu Chen, Daimeng Wei, Hengchao Shang, Jiaxin Guo, Zongyao Li, Minghan Wang, Liangyou Li, Lizhi Lei, Hao Yang, Ying Qin
This paper describes our work in the WAT 2020 Indic Multilingual Translation Task.
no code implementations • WMT (EMNLP) 2020 • Daimeng Wei, Hengchao Shang, Zhanglin Wu, Zhengzhe Yu, Liangyou Li, Jiaxin Guo, Minghan Wang, Hao Yang, Lizhi Lei, Ying Qin, Shiliang Sun
We also conduct experiment with similar language augmentation, which lead to positive results, although not used in our submission.
no code implementations • WMT (EMNLP) 2020 • Hao Yang, Minghan Wang, Daimeng Wei, Hengchao Shang, Jiaxin Guo, Zongyao Li, Lizhi Lei, Ying Qin, Shimin Tao, Shiliang Sun, Yimeng Chen
The paper presents the submission by HW-TSC in the WMT 2020 Automatic Post Editing Shared Task.
no code implementations • WMT (EMNLP) 2020 • Wei Peng, Jianfeng Liu, Minghan Wang, Liangyou Li, Xupeng Meng, Hao Yang, Qun Liu
This paper describes Huawei’s submissions to the WMT20 biomedical translation shared task.
no code implementations • WMT (EMNLP) 2020 • Minghan Wang, Hao Yang, Hengchao Shang, Daimeng Wei, Jiaxin Guo, Lizhi Lei, Ying Qin, Shimin Tao, Shiliang Sun, Yimeng Chen, Liangyou Li
This paper presents our work in the WMT 2020 Word and Sentence-Level Post-Editing Quality Estimation (QE) Shared Task.
no code implementations • EMNLP (BlackboxNLP) 2021 • Minghan Wang, Guo Jiaxin, Yuxia Wang, Yimeng Chen, Su Chang, Hengchao Shang, Min Zhang, Shimin Tao, Hao Yang
Length prediction is a special task in a series of NAT models where target length has to be determined before generation.
no code implementations • MTSummit 2021 • Minghan Wang, Jiaxin Guo, Yimeng Chen, Chang Su, Min Zhang, Shimin Tao, Hao Yang
Based on large-scale pretrained networks and the liability to be easily overfitting with limited labelled training data of multimodal translation (MMT) is a critical issue in MMT.
no code implementations • INLG (ACL) 2021 • Minghan Wang, Guo Jiaxin, Yuxia Wang, Yimeng Chen, Su Chang, Daimeng Wei, Min Zhang, Shimin Tao, Hao Yang
Mask-predict CMLM (Ghazvininejad et al., 2019) has achieved stunning performance among non-autoregressive NMT models, but we find that the mechanism of predicting all of the target words only depending on the hidden state of [MASK] is not effective and efficient in initial iterations of refinement, resulting in ungrammatical repetitions and slow convergence.
no code implementations • WMT (EMNLP) 2021 • Daimeng Wei, Zongyao Li, Zhanglin Wu, Zhengzhe Yu, Xiaoyu Chen, Hengchao Shang, Jiaxin Guo, Minghan Wang, Lizhi Lei, Min Zhang, Hao Yang, Ying Qin
This paper presents the submission of Huawei Translate Services Center (HW-TSC) to the WMT 2021 News Translation Shared Task.
no code implementations • WMT (EMNLP) 2021 • Zongyao Li, Daimeng Wei, Hengchao Shang, Xiaoyu Chen, Zhanglin Wu, Zhengzhe Yu, Jiaxin Guo, Minghan Wang, Lizhi Lei, Min Zhang, Hao Yang, Ying Qin
This paper presents the submission of Huawei Translation Service Center (HW-TSC) to WMT 2021 Triangular MT Shared Task.
no code implementations • WMT (EMNLP) 2021 • Zhengzhe Yu, Daimeng Wei, Zongyao Li, Hengchao Shang, Xiaoyu Chen, Zhanglin Wu, Jiaxin Guo, Minghan Wang, Lizhi Lei, Min Zhang, Hao Yang, Ying Qin
This paper presents the submission of Huawei Translation Services Center (HW-TSC) to the WMT 2021 Large-Scale Multilingual Translation Task.
no code implementations • WMT (EMNLP) 2021 • Hengchao Shang, Ting Hu, Daimeng Wei, Zongyao Li, Jianfei Feng, Zhengzhe Yu, Jiaxin Guo, Shaojun Li, Lizhi Lei, Shimin Tao, Hao Yang, Jun Yao, Ying Qin
This paper presents the submission of Huawei Translation Services Center (HW-TSC) to WMT 2021 Efficiency Shared Task.
no code implementations • WMT (EMNLP) 2021 • Hao Yang, Zhanglin Wu, Zhengzhe Yu, Xiaoyu Chen, Daimeng Wei, Zongyao Li, Hengchao Shang, Minghan Wang, Jiaxin Guo, Lizhi Lei, Chuanfei Xu, Min Zhang, Ying Qin
This paper describes the submission of Huawei Translation Service Center (HW-TSC) to WMT21 biomedical translation task in two language pairs: Chinese↔English and German↔English (Our registered team name is HuaweiTSC).
no code implementations • WMT (EMNLP) 2021 • Yimeng Chen, Chang Su, Yingtao Zhang, Yuxia Wang, Xiang Geng, Hao Yang, Shimin Tao, Guo Jiaxin, Wang Minghan, Min Zhang, Yujia Liu, ShuJian Huang
This paper presents our work in WMT 2021 Quality Estimation (QE) Shared Task.
1 code implementation • 2 Jun 2023 • Daimeng Wei, Zhanglin Wu, Hengchao Shang, Zongyao Li, Minghan Wang, Jiaxin Guo, Xiaoyu Chen, Zhengzhe Yu, Hao Yang
To address this issue, we propose Text Style Transfer Back Translation (TST BT), which uses a style transfer model to modify the source side of BT data.
no code implementations • 28 May 2023 • Hao Yang, Jinming Zhao, Gholamreza Haffari, Ehsan Shareghi
Pre-trained speech encoders have been central to pushing state-of-the-art results across various speech understanding and generation tasks.
no code implementations • 27 May 2023 • Yan Ding, Xiaohan Zhang, Saeid Amiri, Nieqing Cao, Hao Yang, Andy Kaminski, Chad Esselink, Shiqi Zhang
Each situation corresponds to a state instance wherein a robot is potentially unable to complete a task using a solution that normally works.
no code implementations • 23 May 2023 • Hao Yang, Can Gao, Hao Líu, Xinyan Xiao, Yanyan Zhao, Bing Qin
The experimental results show that our model achieves state-of-the-art performance in various downstream tasks, and through ablation study can prove that effective cross-layer learning improves the model's ability of multimodal representation.
no code implementations • 17 May 2023 • Hao Yang, Junyu Gao, Yuan Yuan, Xuelong Li
Anomaly detection in temporal data from sensors under aviation scenarios is a practical but challenging task: 1) long temporal data is difficult to extract contextual information with temporal correlation; 2) the anomalous data are rare in time series, causing normal/abnormal imbalance in anomaly detection, making the detector classification degenerate or even fail.
no code implementations • 11 May 2023 • Aneeq Zia, Kiran Bhattacharyya, Xi Liu, Max Berniker, Ziheng Wang, Rogerio Nespolo, Satoshi Kondo, Satoshi Kasai, Kousuke Hirasawa, Bo Liu, David Austin, Yiheng Wang, Michal Futrega, Jean-Francois Puget, Zhenqiang Li, Yoichi Sato, Ryo Fujii, Ryo Hachiuma, Mana Masuda, Hideo Saito, An Wang, Mengya Xu, Mobarakol Islam, Long Bai, Winnie Pang, Hongliang Ren, Chinedu Nwoye, Luca Sestini, Nicolas Padoy, Maximilian Nielsen, Samuel Schüttler, Thilo Sentker, Hümeyra Husseini, Ivo Baltruschat, Rüdiger Schmitz, René Werner, Aleksandr Matsun, Mugariya Farooq, Numan Saaed, Jose Renato Restom Viera, Mohammad Yaqub, Neil Getty, Fangfang Xia, Zixuan Zhao, Xiaotian Duan, Xing Yao, Ange Lou, Hao Yang, Jintong Han, Jack Noble, Jie Ying Wu, Tamer Abdulbaki Alshirbaji, Nour Aldeen Jalal, Herag Arabian, Ning Ding, Knut Moeller, Weiliang Chen, Quan He, Muhammad Bilal, Taofeek Akinosho, Adnan Qayyum, Massimo Caputo, Hunaid Vohra, Michael Loizou, Anuoluwapo Ajayi, Ilhem Berrou, Faatihah Niyi-Odumosu, Lena Maier-Hein, Danail Stoyanov, Stefanie Speidel, Anthony Jarc
Unfortunately, obtaining the annotations needed to train machine learning models to identify and localize surgical tools is a difficult task.
no code implementations • 11 May 2023 • Zhaoyang Zhang, Yantao Shen, Kunyu Shi, Zhaowei Cai, Jun Fang, Siqi Deng, Hao Yang, Davide Modolo, Zhuowen Tu, Stefano Soatto
We present a sequence-to-sequence vision-language model whose parameters are jointly trained on all tasks (all for one) and fully shared among multiple tasks (one for all), resulting in a single model which we named Musketeer.
no code implementations • 15 Apr 2023 • Kwei-Herng Lai, Lan Wang, Huiyuan Chen, Kaixiong Zhou, Fei Wang, Hao Yang, Xia Hu
We formulate context sampling into the Markov decision process and exploit deep reinforcement learning to optimize the time series domain adaptation process via context sampling and design a tailored reward function to generate domain-invariant features that better align two domains for anomaly detection.
no code implementations • 12 Apr 2023 • Hao Yang, Weijian Huang, Jiarun Liu, Cheng Li, Shanshan Wang
The ability to incrementally learn new classes from limited samples is crucial to the development of artificial intelligence systems for real clinical application.
1 code implementation • 6 Apr 2023 • You Huang, Hao Yang, Ke Sun, Shengchuan Zhang, Guannan Jiang, Rongrong Ji, Liujuan Cao
Second, the model has to repeatedly process the image, the annotator's current click, and the model's feedback of the annotator's former clicks at each step of interaction, resulting in redundant computations.
no code implementations • CVPR 2023 • Hao Yang, Lanqing Hong, Aoxue Li, Tianyang Hu, Zhenguo Li, Gim Hee Lee, LiWei Wang
In this work, we first investigate the effects of synthetic data in synthetic-to-real novel view synthesis and surprisingly observe that models trained with synthetic data tend to produce sharper but less accurate volume densities.
no code implementations • 15 Mar 2023 • Weijian Huang, Hao Yang, Cheng Li, Mingtong Dai, Rui Yang, Shanshan Wang
To this end, we propose a novel medical generalist agent, MGA, that can address three kinds of common clinical tasks via clinical reports knowledge transformation.
no code implementations • 7 Mar 2023 • Yonatan Dukler, Alessandro Achille, Hao Yang, Varsha Vivek, Luca Zancato, Ben Bowman, Avinash Ravichandran, Charless Fowlkes, Ashwin Swaminathan, Stefano Soatto
We show that, even when selecting a single top-scoring adapter, InCA achieves performance comparable to full fine-tuning, at a cost comparable to fine-tuning just the last layer.
no code implementations • CVPR 2023 • Achin Jain, Gurumurthy Swaminathan, Paolo Favaro, Hao Yang, Avinash Ravichandran, Hrayr Harutyunyan, Alessandro Achille, Onkar Dabeer, Bernt Schiele, Ashwin Swaminathan, Stefano Soatto
The PPL improves the performance estimation on average by 37% across 16 classification and 33% across 10 detection datasets, compared to the power law.
no code implementations • 30 Jan 2023 • Zhanglin Wu, Min Zhang, Ming Zhu, Yinglu Li, Ting Zhu, Hao Yang, Song Peng, Ying Qin
BERTScore is an effective and robust automatic metric for referencebased machine translation evaluation.
no code implementations • 19 Jan 2023 • Shizun Wang, Weihong Zeng, Xu Wang, Hao Yang, Li Chen, Yi Yuan, Yunzhao Zeng, Min Zheng, Chuang Zhang, Ming Wu
To this end, we propose SwiftAvatar, a novel avatar auto-creation framework that is evidently superior to previous works.
no code implementations • CVPR 2023 • Hao Li, Charless Fowlkes, Hao Yang, Onkar Dabeer, Zhuowen Tu, Stefano Soatto
With thousands of historical training jobs, a recommendation system can be learned to predict the model selection score given the features of the dataset and the model as input.
no code implementations • 19 Dec 2022 • Yangyu Huang, Xi Chen, Jongyoo Kim, Hao Yang, Chong Li, Jiaolong Yang, Dong Chen
To evaluate our method, we manually label the dense landmarks on 300W testset.
no code implementations • 12 Dec 2022 • Yachao Li, Junhui Li, Jing Jiang, Shimin Tao, Hao Yang, Min Zhang
To alleviate this problem, we propose a position-aware Transformer (P-Transformer) to enhance both the absolute and relative position information in both self-attention and cross-attention.
1 code implementation • 8 Dec 2022 • Jinze Bai, Rui Men, Hao Yang, Xuancheng Ren, Kai Dang, Yichang Zhang, Xiaohuan Zhou, Peng Wang, Sinan Tan, An Yang, Zeyu Cui, Yu Han, Shuai Bai, Wenbin Ge, Jianxin Ma, Junyang Lin, Jingren Zhou, Chang Zhou
As a starting point, we provide presets of 7 different modalities and 23 highly-diverse example tasks in OFASys, with which we also develop a first-in-kind, single model, OFA+, that can handle text, image, speech, video, and motion data.
no code implementations • 8 Dec 2022 • Huiyuan Chen, Xiaoting Li, Kaixiong Zhou, Xia Hu, Chin-Chia Michael Yeh, Yan Zheng, Hao Yang
We found that our TinyKG with INT2 quantization aggressively reduces the memory footprint of activation maps with $7 \times$, only with $2\%$ loss in accuracy, allowing us to deploy KGNNs on memory-constrained devices.
no code implementations • 8 Dec 2022 • Huiyuan Chen, Yusan Lin, Menghai Pan, Lan Wang, Chin-Chia Michael Yeh, Xiaoting Li, Yan Zheng, Fei Wang, Hao Yang
Transformer-based sequential recommenders are very powerful for capturing both short-term and long-term sequential item dependencies.
no code implementations • 2 Dec 2022 • Xiaoting Li, Yuhang Wu, Vineeth Rakesh, Yusan Lin, Hao Yang, Fei Wang
Graph neural networks have achieved significant success in representation learning.
1 code implementation • 24 Oct 2022 • Hao Yang, Jinming Zhao, Gholamreza Haffari, Ehsan Shareghi
Pre-trained speech Transformers have facilitated great success across various speech processing tasks.
no code implementations • 17 Oct 2022 • Han Xu, Menghai Pan, Zhimeng Jiang, Huiyuan Chen, Xiaoting Li, Mahashweta Das, Hao Yang
The existence of adversarial attacks (or adversarial examples) brings huge concern about the machine learning (ML) model's safety issues.
no code implementations • 16 Oct 2022 • Jinming Zhao, Hao Yang, Gholamreza Haffari, Ehsan Shareghi
Pre-trained speech Transformers in speech translation (ST) have facilitated state-of-the-art (SotA) results; yet, using such encoders is computationally expensive.
no code implementations • 4 Oct 2022 • Yan Ding, Xiaohan Zhang, Saeid Amiri, Nieqing Cao, Hao Yang, Chad Esselink, Shiqi Zhang
This paper introduces a novel algorithm (COWP) for open-world task planning and situation handling that dynamically augments the robot's action knowledge with task-oriented common sense.
no code implementations • 13 Sep 2022 • Achin Jain, Kibok Lee, Gurumurthy Swaminathan, Hao Yang, Bernt Schiele, Avinash Ravichandran, Onkar Dabeer
Combined with a matching loss, it can effectively find objects that are similar to the input patch and complete the missing annotations.
no code implementations • CVPR 2023 • Xiaoyi Dong, Jianmin Bao, Yinglin Zheng, Ting Zhang, Dongdong Chen, Hao Yang, Ming Zeng, Weiming Zhang, Lu Yuan, Dong Chen, Fang Wen, Nenghai Yu
Second, masked self-distillation is also consistent with vision-language contrastive from the perspective of training objective as both utilize the visual encoder for feature aligning, and thus is able to learn local semantics getting indirect supervision from the language.
1 code implementation • 4 Aug 2022 • Hao Yang, Junyang Lin, An Yang, Peng Wang, Chang Zhou, Hongxia Yang
Prompt tuning has become a new paradigm for model tuning and it has demonstrated success in natural language pretraining and even vision pretraining.
Ranked #2 on
Visual Entailment
on SNLI-VE test
1 code implementation • 22 Jul 2022 • Kibok Lee, Hao Yang, Satyaki Chakraborty, Zhaowei Cai, Gurumurthy Swaminathan, Avinash Ravichandran, Onkar Dabeer
Most existing works on few-shot object detection (FSOD) focus on a setting where both pre-training and few-shot learning datasets are from a similar domain.
1 code implementation • 21 Jul 2022 • Hao Yang, Chen Shi, Yihong Chen, LiWei Wang
Given a set of point features and image feature maps, DeMF adaptively aggregates image features by taking the projected 2D location of the 3D point as reference.
Ranked #4 on
3D Object Detection
on SUN-RGBD val
1 code implementation • 3 Jul 2022 • Jinming Zhao, Hao Yang, Ehsan Shareghi, Gholamreza Haffari
End-to-end speech-to-text translation models are often initialized with pre-trained speech encoder and pre-trained text decoder.
1 code implementation • 30 Jun 2022 • Kuan Li, Yang Liu, Xiang Ao, Jianfeng Chi, Jinghua Feng, Hao Yang, Qing He
However, both strategies are faced with some immediate problems: raw features cannot represent various properties of nodes (e. g., structure information), and representations learned by supervised GNN may suffer from the poor performance of the classifier on the poisoned graph.
no code implementations • 28 Jun 2022 • Hao Yang, Yanyan Zhao, Jianwei Liu, Yang Wu, Bing Qin
In this paper, we propose a new dataset, the Multimodal Aspect-Category Sentiment Analysis (MACSA) dataset, which contains more than 21K text-image pairs.
no code implementations • 19 Jun 2022 • Meng-Ju Tsai, Zhiyong Cui, Hao Yang, Cole Kopca, Sophie Tien, Yinhai Wang
To better manage future roadway capacity and accommodate social and human impacts, it is crucial to propose a flexible and comprehensive framework to predict physical-aware long-term traffic conditions for public users and transportation agencies.
no code implementations • 4 Jun 2022 • Yuezihan Jiang, Hao Yang, Junyang Lin, Hanyu Zhao, An Yang, Chang Zhou, Hongxia Yang, Zhi Yang, Bin Cui
Prompt Learning has recently gained great popularity in bridging the gap between pretraining tasks and various downstream tasks.
no code implementations • 4 May 2022 • Yi Liang, Shuai Zhao, Bo Cheng, Yuwei Yin, Hao Yang
Few-shot relation learning refers to infer facts for relations with a limited number of observed triples.
1 code implementation • NAACL 2022 • Chun Zeng, Jiangjie Chen, Tianyi Zhuang, Rui Xu, Hao Yang, Ying Qin, Shimin Tao, Yanghua Xiao
To this end, we propose a plug-in algorithm for this line of work, i. e., Aligned Constrained Training (ACT), which alleviates this problem by familiarizing the model with the source-side context of the constraints.
1 code implementation • 25 Apr 2022 • Hao Ouyang, Bo Zhang, Pan Zhang, Hao Yang, Jiaolong Yang, Dong Chen, Qifeng Chen, Fang Wen
We propose pose-guided multiplane image (MPI) synthesis which can render an animatable character in real scenes with photorealistic quality.
1 code implementation • CVPR 2022 • Pei Wang, Zhaowei Cai, Hao Yang, Gurumurthy Swaminathan, Nuno Vasconcelos, Bernt Schiele, Stefano Soatto
This is enabled by a unified architecture, Omni-DETR, based on the recent progress on student-teacher framework and end-to-end transformer based object detection.
Ranked #12 on
Semi-Supervised Object Detection
on COCO 2% labeled data
2 code implementations • CVPR 2022 • Dengpan Fu, Dongdong Chen, Hao Yang, Jianmin Bao, Lu Yuan, Lei Zhang, Houqiang Li, Fang Wen, Dong Chen
Since theses ID labels automatically derived from tracklets inevitably contain noises, we develop a large-scale Pre-training framework utilizing Noisy Labels (PNL), which consists of three learning modules: supervised Re-ID learning, prototype-based contrastive learning, and label-guided contrastive learning.
Ranked #7 on
Person Re-Identification
on CUHK03
1 code implementation • Findings (ACL) 2022 • Yang Wu, Yanyan Zhao, Hao Yang, Song Chen, Bing Qin, Xiaohuan Cao, Wenting Zhao
Through further analysis of the ASR outputs, we find that in some cases the sentiment words, the key sentiment elements in the textual modality, are recognized as other words, which makes the sentiment of the text change and hurts the performance of multimodal sentiment models directly.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
no code implementations • 13 Jan 2022 • Lan Wang, Yusan Lin, Yuhang Wu, Huiyuan Chen, Fei Wang, Hao Yang
Today's cyber-world is vastly multivariate.
Time Series Anomaly Detection
Unsupervised Anomaly Detection
no code implementations • 1 Jan 2022 • Hao Yang, Min Wang, Zhengfei Yu, Yun Zhou
Extensive experiments on well-known white- and black-box attacks show that MFDV-SNN achieves a significant improvement over existing methods, which indicates that it is a simple but effective method to improve model robustness.
no code implementations • EAMT 2022 • Minghan Wang, Jiaxin Guo, Yuxia Wang, Daimeng Wei, Hengchao Shang, Chang Su, Yimeng Chen, Yinglu Li, Min Zhang, Shimin Tao, Hao Yang
In this paper, we aim to close the gap by preserving the original objective of AR and NAR under a unified framework.
no code implementations • 22 Dec 2021 • Zhengzhe Yu, Jiaxin Guo, Minghan Wang, Daimeng Wei, Hengchao Shang, Zongyao Li, Zhanglin Wu, Yuxia Wang, Yimeng Chen, Chang Su, Min Zhang, Lizhi Lei, Shimin Tao, Hao Yang
Deep encoders have been proven to be effective in improving neural machine translation (NMT) systems, but it reaches the upper bound of translation quality when the number of encoder layers exceeds 18.
no code implementations • 22 Dec 2021 • Jiaxin Guo, Minghan Wang, Daimeng Wei, Hengchao Shang, Yuxia Wang, Zongyao Li, Zhengzhe Yu, Zhanglin Wu, Yimeng Chen, Chang Su, Min Zhang, Lizhi Lei, Shimin Tao, Hao Yang
An effective training strategy to improve the performance of AT models is Self-Distillation Mixup (SDM) Training, which pre-trains a model on raw data, generates distilled data by the pre-trained model itself and finally re-trains a model on the combination of raw data and distilled data.
1 code implementation • CVPR 2022 • Yinglin Zheng, Hao Yang, Ting Zhang, Jianmin Bao, Dongdong Chen, Yangyu Huang, Lu Yuan, Dong Chen, Ming Zeng, Fang Wen
In this paper, we study the transfer performance of pre-trained models on face analysis tasks and introduce a framework, called FaRL, for general Facial Representation Learning in a visual-linguistic manner.
Ranked #1 on
Face Parsing
on CelebAMask-HQ
(using extra training data)
1 code implementation • NeurIPS 2021 • Wenqing Zheng, Qiangqiang Guo, Hao Yang, Peihao Wang, Zhangyang Wang
This paper presents the Delayed Propagation Transformer (DePT), a new transformer-based model that specializes in the global modeling of CPS while taking into account the immutable constraints from the physical world.
no code implementations • 29 Sep 2021 • Hao Zhu, Mahashweta Das, Mangesh Bendre, Fei Wang, Hao Yang, Soha Hassoun
In this work, we propose an adversarial training based modification to the current state-of-the-arts link prediction method to solve this problem.
1 code implementation • ICCV 2021 • Yangyu Huang, Hao Yang, Chong Li, Jongyoo Kim, Fangyun Wei
On the other hand, AAM is an attention module which can get anisotropic attention mask focusing on the region of point and its local edge connected by adjacent points, it has a stronger response in tangent than in normal, which means relaxed constraints in the tangent.
Ranked #3 on
Face Alignment
on 300W
no code implementations • 31 Aug 2021 • Javid Ebrahimi, Hao Yang, Wei zhang
Adversarial training (AT) is one of the most reliable methods for defending against adversarial attacks in machine learning.
no code implementations • 15 Aug 2021 • Yuhang Wu, Mengting Gu, Lan Wang, Yusan Lin, Fei Wang, Hao Yang
Modeling inter-dependencies between time-series is the key to achieve high performance in anomaly detection for multivariate time-series data.
no code implementations • 9 Aug 2021 • Minghan Wang, Yuxia Wang, Chang Su, Jiaxin Guo, Yingtao Zhang, Yujia Liu, Min Zhang, Shimin Tao, Xingshan Zeng, Liangyou Li, Hao Yang, Ying Qin
This paper describes our work in participation of the IWSLT-2021 offline speech translation task.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+5
no code implementations • 27 Jul 2021 • Hao Yang, Tavan Eftekhar, Chad Esselink, Yan Ding, Shiqi Zhang
Everyday tasks are characterized by their varieties and variations, and frequently are not clearly specified to service agents.
1 code implementation • journal 2021 • Qing Ding, Liquan Shen, Liangwei Yu, Hao Yang, Mai Xu
To overcome these limitations, we propose a patch-wise spatial-temporal quality enhancement network which firstly extracts spatial and temporal features, then recalibrates and fuses the obtained spatial and temporal features.
1 code implementation • NeurIPS 2021 • Prince Osei Aboagye, Jeff Phillips, Yan Zheng, Chin-Chia Michael Yeh, Junpeng Wang, Wei zhang, Liang Wang, Hao Yang
Learning a good transfer function to map the word vectors from two languages into a shared cross-lingual word vector space plays a crucial role in cross-lingual NLP.
1 code implementation • The Web Conference 2021 • Yang Liu1, Xiang Ao, Zidi Qin, Jianfeng Chi, Jinghua Feng, Hao Yang, Qing He
Graph-based fraud detection approaches have escalated lots of attention recently due to the abundant relational information of graph-structured data, which may be beneficial for the detection of fraudsters.
Ranked #3 on
Node Classification
on Amazon-Fraud
no code implementations • 1 Apr 2021 • Xu Wang, Shuai Zhao, Bo Cheng, Jiale Han, Yingting Li, Hao Yang, Ivan Sekulic, Guoshun Nan
Question Answering (QA) models over Knowledge Bases (KBs) are capable of providing more precise answers by utilizing relation information among entities.
no code implementations • 1 Apr 2021 • Hao Yang, Youzhi Jin, Ziyin Li, Deng-Bao Wang, Lei Miao, Xin Geng, Min-Ling Zhang
During the training process, DLT records the loss value of each sample and calculates dynamic loss thresholds.
1 code implementation • CVPR 2021 • Chulin Xie, Chuxin Wang, Bo Zhang, Hao Yang, Dong Chen, Fang Wen
In this paper, we proposed a novel Style-based Point Generator with Adversarial Rendering (SpareNet) for point cloud completion.
Ranked #1 on
Point Cloud Completion
on ShapeNet
(Earth Mover's Distance metric)
no code implementations • 9 Feb 2021 • Liuyihan Song, Pan Pan, Kang Zhao, Hao Yang, Yiming Chen, Yingya Zhang, Yinghui Xu, Rong Jin
In the last decades, extreme classification has become an essential topic for deep learning.
no code implementations • ICCV 2021 • Ahmed Abusnaina, Yuhang Wu, Sunpreet Arora, Yizhen Wang, Fei Wang, Hao Yang, David Mohaisen
We present the first graph-based adversarial detection method that constructs a Latent Neighborhood Graph (LNG) around an input example to determine if the input example is adversarial.
no code implementations • ICLR 2021 • Benyou Wang, Lifeng Shang, Christina Lioma, Xin Jiang, Hao Yang, Qun Liu, Jakob Grue Simonsen
Various Position Embeddings (PEs) have been proposed in Transformer based architectures~(e. g. BERT) to model word order.
no code implementations • 31 Dec 2020 • Yuhang Wu, Sunpreet S. Arora, Yanhong Wu, Hao Yang
Adversarial examples are input examples that are specifically crafted to deceive machine learning classifiers.
1 code implementation • CVPR 2021 • Dengpan Fu, Dongdong Chen, Jianmin Bao, Hao Yang, Lu Yuan, Lei Zhang, Houqiang Li, Dong Chen
In this paper, we present a large scale unlabeled person re-identification (Re-ID) dataset "LUPerson" and make the first attempt of performing unsupervised pre-training for improving the generalization ability of the learned person Re-ID feature representation.
Ranked #2 on
Person Re-Identification
on Market-1501
(using extra training data)
no code implementations • COLING 2020 • Xu Wang, Shuai Zhao, Jiale Han, Bo Cheng, Hao Yang, Jianchang Ao, Zhenzi Li
The structural information of Knowledge Bases (KBs) has proven effective to Question Answering (QA).
no code implementations • 27 Nov 2020 • Hao Yang, Wojciech Roga, Jonathan D. Pritchard, John Jeffers
We use the continuous-variable Gaussian quantum information formalism to show that quantum illumination is better for object detection compared with coherent states of the same mean photon number, even for simple direct photodetection.
Object Detection
Quantum Physics
no code implementations • 5 Aug 2020 • Weijian Huang, Hao Yang, Xinfeng Liu, Cheng Li, Ian Zhang, Rongpin Wang, Hairong Zheng, Shan-Shan Wang
Multi-contrast magnetic resonance (MR) image registration is useful in the clinic to achieve fast and accurate imaging-based disease diagnosis and treatment planning.
no code implementations • 2 Aug 2020 • Ruimin Ke, Zhiyong Cui, Yanlong Chen, Meixin Zhu, Hao Yang, Yinhai Wang
It is among the first efforts in applying edge computing for real-time traffic video analytics and is expected to benefit multiple sub-fields in smart transportation research and applications.
no code implementations • WS 2020 • Minghan Wang, Hao Yang, Yao Deng, Ying Qin, Lizhi Lei, Daimeng Wei, Hengchao Shang, Ning Xie, Xiaochun Li, Jiaxian Guo
The paper presents details of our system in the IWSLT Video Speech Translation evaluation.
no code implementations • 18 Jun 2020 • Hu Liu, Jing Lu, Hao Yang, Xiwei Zhao, Sulong Xu, Hao Peng, Zehua Zhang, Wenjie Niu, Xiaokun Zhu, Yongjun Bao, Weipeng Yan
Existing algorithms usually extract visual features using off-the-shelf Convolutional Neural Networks (CNNs) and late fuse the visual and non-visual features for the finally predicted CTR.
1 code implementation • 5 Jun 2020 • Aravind Sankar, Yanhong Wu, Yuhang Wu, Wei zhang, Hao Yang, Hari Sundaram
We study the problem of making item recommendations to ephemeral groups, which comprise users with limited or no historical activities together.
no code implementations • 21 May 2020 • Adit Krishnan, Mahashweta Das, Mangesh Bendre, Hao Yang, Hari Sundaram
The rapid proliferation of new users and items on the social web has aggravated the gray-sheep user/long-tail item challenge in recommender systems.
no code implementations • 13 May 2020 • Maryam Moosaei, Yusan Lin, Hao Yang
There are a few approaches that consider an entire outfit, but these approaches have limitations such as requiring rich semantic information, category labels, and fixed order of items.
no code implementations • 24 Mar 2020 • Dinh-Luan Nguyen, Sunpreet S. Arora, Yuhang Wu, Hao Yang
While feasible, digital attacks have limited applicability in attacking deployed systems, including face recognition systems, where an adversary typically has access to the input and not the transmission channel.
no code implementations • 17 Mar 2020 • Hao Yang, Dan Yan, Li Zhang, Dong Li, YunDa Sun, ShaoDi You, Stephen J. Maybank
It transmits the high-level semantic features to the low-level layers and flows temporal information stage by stage to progressively model global spatial-temporal features for action recognition; (3) The FGCN model provides early predictions.
Ranked #28 on
Skeleton Based Action Recognition
on NTU RGB+D 120
1 code implementation • ICLR 2020 • Hao Li, Pratik Chaudhari, Hao Yang, Michael Lam, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto
Our findings challenge common practices of fine-tuning and encourages deep learning practitioners to rethink the hyperparameters for fine-tuning.
no code implementations • 13 Feb 2020 • Xialei Liu, Hao Yang, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto
For the difficult cases, where the domain gaps and especially category differences are large, we explore three different exemplar sampling methods and show the proposed adaptive sampling method is effective to select diverse and informative samples from entire datasets, to further prevent forgetting.
8 code implementations • 31 Dec 2019 • Lingzhi Li, Jianmin Bao, Hao Yang, Dong Chen, Fang Wen
We propose a novel attributes encoder for extracting multi-level target face attributes, and a new generator with carefully designed Adaptive Attentional Denormalization (AAD) layers to adaptively integrate the identity and the attributes for face synthesis.
4 code implementations • CVPR 2020 • Lingzhi Li, Jianmin Bao, Ting Zhang, Hao Yang, Dong Chen, Fang Wen, Baining Guo
For this reason, face X-ray provides an effective way for detecting forgery generated by most existing face manipulation algorithms.
no code implementations • 22 Aug 2019 • Manoj Reddy Dareddy, Mahashweta Das, Hao Yang
Supervised machine learning tasks in networks such as node classification and link prediction require us to perform feature engineering that is known and agreed to be the key to success in applied machine learning.
no code implementations • ICCV 2019 • Hao Yang, Hao Wu, Hao Chen
However, these methods require fully annotated object bounding boxes for training, which are incredibly hard to scale up due to the high annotation cost.
1 code implementation • 23 Jul 2019 • Yaxiong Wang, Hao Yang, Xueming Qian, Lin Ma, Jing Lu, Biao Li, Xin Fan
Then, an attention mechanism is proposed to model the relations between the image region and blocks and generate the valuable position feature, which will be further utilized to enhance the region expression and model a more reliable relationship between the visual image and the textual sentence.
1 code implementation • 16 Jul 2019 • Kehan Qi, Hao Yang, Cheng Li, Zaiyi Liu, Meiyun Wang, Qiegen Liu, Shan-Shan Wang
Recently, approaches based on deep learning and methods for contextual information extraction have served in many image segmentation tasks.
2 code implementations • 16 Jul 2019 • Hao Yang, Weijian Huang, Kehan Qi, Cheng Li, Xinfeng Liu, Meiyun Wang, Hairong Zheng, Shan-Shan Wang
To address these challenges, this paper proposes a Cross-Level fusion and Context Inference Network (CLCI-Net) for the chronic stroke lesion segmentation from T1-weighted MR images.
no code implementations • 16 Jul 2019 • Yusan Lin, Hao Yang
Fashion is a large and fast-changing industry.
2 code implementations • CVPR 2019 • Jinpeng Lin, Hao Yang, Dong Chen, Ming Zeng, Fang Wen, Lu Yuan
It uses hierarchical local based method for inner facial components and global methods for outer facial components.
1 code implementation • 31 May 2019 • Bonggun Shin, Hao Yang, Jinho D. Choi
Recent advances in deep learning have facilitated the demand of neural models for real applications.
Ranked #2 on
Sentiment Analysis
on MPQA
no code implementations • CVPR 2019 • Shuyang Gu, Jianmin Bao, Hao Yang, Dong Chen, Fang Wen, Lu Yuan
Portrait editing is a popular subject in photo manipulation.
no code implementations • 4 Feb 2019 • Zhongliang Yang, Hao Yang, Yuting Hu, Yongfeng Huang, Yu-Jin Zhang
To solve these two challenges, in this paper, combined with the sliding window detection algorithm and Convolution Neural Network we propose a real-time VoIP steganalysis method which based on multi-channel convolution sliding windows.
2 code implementations • 22 Dec 2018 • Aravind Sankar, Yanhong Wu, Liang Gou, Wei zhang, Hao Yang
Learning latent representations of nodes in graphs is an important and ubiquitous task with widespread applications such as link prediction, node classification, and graph visualization.
no code implementations • WS 2018 • Sizhen Li, Shuai Zhao, Bo Cheng, Hao Yang
With huge amount of information generated every day on the web, fact checking is an important and challenging task which can help people identify the authenticity of most claims as well as providing evidences selected from knowledge source like Wikipedia.
no code implementations • ECCV 2018 • Qingyi Tao, Hao Yang, Jianfei Cai
Object detection is one of the major problems in computer vision, and has been extensively studied.
no code implementations • 27 Jul 2017 • Qingyi Tao, Hao Yang, Jianfei Cai
Object detection without bounding box annotations, i. e, weakly supervised detection methods, are still lagging far behind.
Ranked #17 on
Weakly Supervised Object Detection
on PASCAL VOC 2012 test
(using extra training data)
no code implementations • CVPR 2017 • Hao Yang, Joey Tianyi Zhou, Jianfei Cai, Yew Soon Ong
As the proposed PI loss is convex and SGD compatible and the framework itself is a fully convolutional network, MIML-FCN+ can be easily integrated with state of-the-art deep learning networks.
no code implementations • 4 Aug 2016 • Hao Yang, Joey Tianyi Zhou, Jianfei Cai
Experimental results demonstrate the effectiveness of the proposed semantic descriptor and the usefulness of incorporating the structured semantic correlations.
no code implementations • CVPR 2016 • Hao Yang, HUI ZHANG
We propose a method to recover the shape of a 3D room from a full-view indoor panorama.
no code implementations • 18 Jan 2016 • Ying Huang, Hong Zheng, Haibin Ling, Erik Blasch, Hao Yang
Bird strikes present a huge risk for aircraft, especially since traditional airport bird surveillance is mainly dependent on inefficient human observation.
no code implementations • CVPR 2016 • Hao Yang, Joey Tianyi Zhou, Yu Zhang, Bin-Bin Gao, Jianxin Wu, Jianfei Cai
With strong labels, our framework is able to achieve state-of-the-art results in both datasets.
Ranked #16 on
Multi-Label Classification
on PASCAL VOC 2007
no code implementations • 19 May 2014 • Chao Zhang, Hong-cen Mei, Hao Yang
A large number of experimental data shows that Support Vector Machine (SVM) algorithm has obvious advantages in text classification, handwriting recognition, image classification, bioinformatics, and some other fields.