1 code implementation • SemEval (NAACL) 2022 • Long Ma, Xiaorong Jian, Xuan Li
This paper describes our system used in the SemEval-2022 Task 11 Multilingual Complex Named Entity Recognition, achieving 3rd for track 1 on the leaderboard.
no code implementations • 13 Apr 2024 • Chengpei Xu, Hao Fu, Long Ma, Wenjing Jia, Chengqi Zhang, Feng Xia, Xiaoyu Ai, Binghao Li, Wenjie Zhang
Localizing text in low-light environments is challenging due to visual degradations.
no code implementations • 4 Feb 2024 • Long Ma, Yuanfei Wang, Fangwei Zhong, Song-Chun Zhu, Yizhou Wang
To do so, it is crucial for the agent to efficiently probe and identify the peer's strategy, as this is the prerequisite for carrying out the best response in adaptation.
no code implementations • 3 Feb 2024 • Long Ma, Jiajia Zhang, Hongping Deng, Ningyu Zhang, Yong Liao, Haiyang Yu
The escalating quality of video generated by advanced video generation methods leads to new security challenges in society, which makes generated video detection an urgent research priority.
no code implementations • 31 Dec 2023 • Xingyuan Li, Yang Zou, JinYuan Liu, Zhiying Jiang, Long Ma, Xin Fan, Risheng Liu
With the rapid progression of deep learning technologies, multi-modality image fusion has become increasingly prevalent in object detection tasks.
no code implementations • 18 Nov 2023 • Haoran Li, Long Ma, Yong Liao, Lechao Cheng, Yanbin Hao, Pengyuan Zhou
First, we segment the objects and the background in a multi-object image.
no code implementations • 7 Sep 2023 • Xiaohan Cui, Long Ma, Tengyu Ma, JinYuan Liu, Xin Fan, Risheng Liu
In this work, we try to arouse the potential of enhancer + detector.
no code implementations • 2 Sep 2023 • Gehui Li, JinYuan Liu, Long Ma, Zhiying Jiang, Xin Fan, Risheng Liu
To overcome these limitations, we propose a Macro-Micro-Hierarchical transformer, which consists of a macro attention to capture long-range dependencies, a micro attention to extract local features, and a hierarchical structure for coarse-to-fine correction.
no code implementations • 22 Aug 2023 • Di Wang, JinYuan Liu, Long Ma, Risheng Liu, Xin Fan
Both stages directly estimate the respective target deformation fields.
3 code implementations • 8 Aug 2023 • Zhu Liu, JinYuan Liu, Benzhuang Zhang, Long Ma, Xin Fan, Risheng Liu
We first conduct systematic analyses about the components of image fusion, investigating the correlation with segmentation robustness under adversarial perturbations.
Ranked #16 on Thermal Image Segmentation on MFN Dataset
1 code implementation • 7 Aug 2023 • Yingchi Liu, Zhu Liu, Long Ma, JinYuan Liu, Xin Fan, Zhongxuan Luo, Risheng Liu
In this study, we propose a generic low-light vision solution by introducing a generative block to convert data from the RAW to the RGB domain.
2 code implementations • ICCV 2023 • JinYuan Liu, Zhu Liu, Guanyao Wu, Long Ma, Risheng Liu, Wei Zhong, Zhongxuan Luo, Xin Fan
Multi-modality image fusion and segmentation play a vital role in autonomous driving and robotic operation.
Ranked #3 on Semantic Segmentation on FMB Dataset
1 code implementation • 2 Jun 2023 • Long Ma, Dian Jin, Nan An, JinYuan Liu, Xin Fan, Risheng Liu
A bilevel learning framework is constructed to endow the scene-irrelevant generality of the encoder towards diverse scenes (i. e., freezing the encoder in the adaptation and testing phases).
no code implementations • 21 May 2023 • Shubo Lv, Xiong Wang, Sining Sun, Long Ma, Lei Xie
Real-world complex acoustic environments especially the ones with a low signal-to-noise ratio (SNR) will bring tremendous challenges to a keyword spotting (KWS) system.
no code implementations • 18 May 2023 • Xingyuan Li, JinYuan Liu, Yixin Lei, Long Ma, Xin Fan, Risheng Liu
3D object detection plays a crucial role in numerous intelligent vision systems.
2 code implementations • 11 May 2023 • Zhu Liu, JinYuan Liu, Guanyao Wu, Long Ma, Xin Fan, Risheng Liu
Recently, multi-modality scene perception tasks, e. g., image fusion and scene understanding, have attracted widespread attention for intelligent vision systems.
1 code implementation • 10 May 2023 • Long Ma, Kai Lu, Tianbo Che, Hailong Huang, Weiguo Gao, Xuan Li
The MultiCoNER II task aims to detect complex, ambiguous, and fine-grained named entities in low-context situations and noisy scenarios like the presence of spelling mistakes and typos for multiple languages.
no code implementations • 24 Apr 2023 • Long Ma, Piet Van Mieghem, Maksim Kitsak
Motivated by the desire to enhance epidemic forecasts, we develop a statistical framework to detect, uncover, and remove reporting delays in the infectious, recovered, and deceased epidemic time series.
no code implementations • 16 Mar 2023 • Yanzhe Fu, Yueteng Kang, Songjun Cao, Long Ma
In this work, we propose a two-stage knowledge distillation method to solve these two problems: the first step is to make the big and non-streaming teacher model smaller, and the second step is to make it streaming.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • 17 Jan 2023 • Zhanheng Yang, Sining Sun, Xiong Wang, Yike Zhang, Long Ma, Lei Xie
In this paper, we propose an efficient approach to obtain a high quality contextual list for a unified streaming/non-streaming based E2E model.
no code implementations • 29 Dec 2022 • Long Ma, Tianjiao Ma, Xinwei Xue, Xin Fan, Zhongxuan Luo, Risheng Liu
Improving the visual quality of the given degraded observation by correcting exposure level is a fundamental task in the computer vision community.
1 code implementation • 19 Nov 2022 • Di Wang, Long Ma, Risheng Liu, Xin Fan
To address the above limitations, we develop an efficient and compact enhancement network in collaboration with a high-level semantic-aware pretrained model, aiming to exploit its hierarchical feature representation as an auxiliary for the low-level underwater image enhancement.
no code implementations • 19 Nov 2022 • Xinwei Xue, Gaoyu Wang, Long Ma, Qi Jia, Yi Wang
In this paper, we design an adjacent slice feature fusion model to introduce information from adjacent slices.
no code implementations • 3 Jul 2022 • Kun Wei, Yike Zhang, Sining Sun, Lei Xie, Long Ma
Then, during the training of the conversational ASR system, the extractor will be frozen to extract the textual representation of preceding speech, while such representation is used as context fed to the ASR decoder through attention mechanism.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
1 code implementation • CVPR 2022 • Long Ma, Tengyu Ma, Risheng Liu, Xin Fan, Zhongxuan Luo
Existing low-light image enhancement techniques are mostly not only difficult to deal with both visual quality and computational efficiency but also commonly invalid in unknown complex scenarios.
no code implementations • 9 Mar 2022 • Yike Zhang, Xiaobing Feng, Yi Liu, Songjun Cao, Long Ma
Automatic speech recognition (ASR) systems used on smart phones or vehicles are usually required to process speech queries from very different domains.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +4
1 code implementation • 22 Feb 2022 • Keqi Deng, Songjun Cao, Yike Zhang, Long Ma, Gaofeng Cheng, Ji Xu, Pengyuan Zhang
Recently, end-to-end automatic speech recognition models based on connectionist temporal classification (CTC) have achieved impressive results, especially when fine-tuned from wav2vec2. 0 models.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +4
no code implementations • 16 Feb 2022 • Kun Wei, Yike Zhang, Sining Sun, Lei Xie, Long Ma
Conversational automatic speech recognition (ASR) is a task to recognize conversational speech including multiple speakers.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +3
no code implementations • 14 Dec 2021 • Keqi Deng, Songjun Cao, Yike Zhang, Long Ma
In our framework, the encoder is initialized with a pretrained AM (wav2vec2. 0).
Automatic Speech Recognition Automatic Speech Recognition (ASR) +3
1 code implementation • 9 Dec 2021 • Long Ma, Risheng Liu, Jiaao Zhang, Xin Fan, Zhongxuan Luo
Further, by sharing an encoder for these two components, we obtain a more lightweight version (SLiteCSDNet for short).
1 code implementation • 9 Dec 2021 • Risheng Liu, Long Ma, Tengyu Ma, Xin Fan, Zhongxuan Luo
To partially address above issues, we establish Retinex-inspired Unrolling with Architecture Search (RUAS), a general learning framework, which not only can address low-light enhancement task, but also has the flexibility to handle other more challenging downstream vision applications.
no code implementations • 15 Sep 2021 • Songjun Cao, Yueteng Kang, Yanzhe Fu, Xiaoshuo Xu, Sining Sun, Yike Zhang, Long Ma
Under such a framework, the neural network is usually pre-trained with massive unlabeled data and then fine-tuned with limited labeled data.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • 15 Sep 2021 • Keqi Deng, Songjun Cao, Long Ma
For the former task, a standard deviation constraint loss (SDC-loss) based end-to-end (E2E) architecture is proposed to identify accents under the same language.
no code implementations • 7 Jul 2021 • Songjun Cao, Yike Zhang, Xiaobing Feng, Long Ma
Secondly, a group of geo-specific language models (Geo-LMs) are integrated into our speech recognition system to improve recognition accuracy of long tail and homophone POI.
1 code implementation • CVPR 2021 • Risheng Liu, Long Ma, Jiaao Zhang, Xin Fan, Zhongxuan Luo
Low-light image enhancement plays very important roles in low-level vision field.
no code implementations • 1 May 2020 • Baiji Liu, Songjun Cao, Sining Sun, Weibin Zhang, Long Ma
Experiments on AISHELL-1 data show that the proposed model, along with the training strategies, improve the character error rate (CER) of MoChA from 8. 96% to 7. 68% on test set.
no code implementations • 17 Jul 2019 • Risheng Liu, Long Ma, Yuxi Zhang, Xin Fan, Zhongxuan Luo
Plenty of experimental results of underexposed image correction demonstrate that our proposed method performs favorably against the state-of-the-art methods on both subjective and objective assessments.
no code implementations • 6 Jul 2019 • Risheng Liu, Long Ma, Xiaoming Yuan, Shangzhi Zeng, Jin Zhang
This paper firstly proposes a convex bilevel optimization paradigm to formulate and optimize popular learning and vision problems in real-world scenarios.
no code implementations • NeurIPS 2018 • Risheng Liu, Shichao Cheng, Xiaokun Liu, Long Ma, Xin Fan, Zhongxuan Luo
Different from these existing network based iterations, which often lack theoretical investigations, we provide strict convergence analysis for PODM in the challenging nonconvex and nonsmooth scenarios.
no code implementations • 5 Nov 2018 • Yiyang Wang, Risheng Liu, Long Ma, Xiaoliang Song
Integrating both numerical algorithms and advanced techniques together, TECU is proposed in a unified framework for solving a class of non-convex problems.
1 code implementation • 9 Oct 2018 • Risheng Liu, Long Ma, Yiyang Wang, Lei Zhang
Enhancing visual qualities of images plays very important roles in various vision and learning applications.