no code implementations • EMNLP 2020 • Hongzhi Zhang, Yingyao Wang, Sirui Wang, Xuezhi Cao, Fuzheng Zhang, Zhongyuan Wang
Verifying fact on semi-structured evidence like tables requires the ability to encode structural information and perform symbolic reasoning.
1 code implementation • COLING 2022 • Zhongyuan Wang, YiXuan Wang, Shaolei Wang, Wanxiang Che
Supervised methods have achieved remarkable results in disfluency detection.
1 code implementation • 14 Oct 2024 • Zhangchi Feng, Dongdong Kuang, Zhongyuan Wang, Zhijie Nie, Yaowei Zheng, Richong Zhang
The second is simple deployment.
2 code implementations • 27 Sep 2024 • Xinlong Wang, Xiaosong Zhang, Zhengxiong Luo, Quan Sun, Yufeng Cui, Jinsheng Wang, Fan Zhang, Yueze Wang, Zhen Li, Qiying Yu, Yingli Zhao, Yulong Ao, Xuebin Min, Tao Li, Boya Wu, Bo Zhao, BoWen Zhang, Liangdong Wang, Guang Liu, Zheqi He, Xi Yang, Jingjing Liu, Yonghua Lin, Tiejun Huang, Zhongyuan Wang
While next-token prediction is considered a promising path towards artificial general intelligence, it has struggled to excel in multimodal tasks, which are still dominated by diffusion models (e. g., Stable Diffusion) and compositional approaches (e. g., CLIP combined with LLMs).
Ranked #104 on Visual Question Answering on MM-Vet
no code implementations • 30 Aug 2024 • Zhongyuan Wang, Richong Zhang, Zhijie Nie, Jaein Kim
To address these challenges, we propose a tool-assisted agent framework for SQL inspection and refinement, equipping the LLM-based agent with two specialized tools: a retriever and a detector, designed to diagnose and correct SQL queries with database mismatches.
no code implementations • 30 Aug 2024 • Jikang Cheng, Zhiyuan Yan, Ying Zhang, Yuhao Luo, Zhongyuan Wang, Chen Li
The accumulation of forgery information should be oriented and progressively increasing during this transition process.
no code implementations • 13 Aug 2024 • Jikang Cheng, Ying Zhang, Zhongyuan Wang, Zou Qin, Chen Li
Recent years have seen an increasing interest in physical adversarial attacks, which aim to craft deployable patterns for deceiving deep neural networks, especially for person detectors.
no code implementations • 13 Aug 2024 • Jikang Cheng, Jiaxin Ai, Zhen Han, Chao Liang, Qin Zou, Zhongyuan Wang, Qian Wang
To achieve visual forensics and target face attribution, we propose a novel task named face retracing, which considers retracing the original target face from the given fake one via inverse mapping.
no code implementations • 13 Aug 2024 • Jikang Cheng, Ying Zhang, Qin Zou, Zhiyuan Yan, Chao Liang, Zhongyuan Wang, Chen Li
Learning intrinsic bias from limited data has been considered the main reason for the failure of deepfake detection with generalizability.
no code implementations • 3 Jul 2024 • Xiang Li, Yiqun Yao, Xin Jiang, Xuezhi Fang, Chao Wang, Xinzhang Liu, Zihan Wang, Yu Zhao, Xin Wang, Yuyao Huang, Shuangyong Song, Yongxiang Li, Zheng Zhang, Bo Zhao, Aixin Sun, Yequan Wang, Zhongjiang He, Zhongyuan Wang, Xuelong Li, Tiejun Huang
Large Language Models (LLMs) represent a significant stride toward Artificial General Intelligence.
no code implementations • 26 Jun 2024 • Jiafeng Liang, Shixin Jiang, Zekun Wang, Haojie Pan, Zerui Chen, Zheng Chu, Ming Liu, Ruiji Fu, Zhongyuan Wang, Bing Qin
Our proposed benchmark consists of three sub-tasks to evaluate comprehension ability of models: (1) Step Captioning: models have to generate captions for specific steps from videos.
no code implementations • 24 May 2024 • Chenxi Sun, Hongzhi Zhang, Zijia Lin, Jingyuan Zhang, Fuzheng Zhang, Zhongyuan Wang, Bin Chen, Chengru Song, Di Zhang, Kun Gai, Deyi Xiong
The core of our approach is the observation that a pre-trained language model can confidently predict multiple contiguous tokens, forming the basis for a \textit{lexical unit}, in which these contiguous tokens could be decoded in parallel.
no code implementations • 24 May 2024 • Guibao Shen, Luozhou Wang, Jiantao Lin, Wenhang Ge, Chaozhe Zhang, Xin Tao, Yuan Zhang, Pengfei Wan, Zhongyuan Wang, Guangyong Chen, Yijun Li, Ying-Cong Chen
In this paper, we introduce the Scene Graph Adapter(SG-Adapter), leveraging the structured representation of scene graphs to rectify inaccuracies in the original text embeddings.
1 code implementation • CVPR 2024 • Sixian Zhang, Bohan Wang, Junqiang Wu, Yan Li, Tingting Gao, Di Zhang, Zhongyuan Wang
Current metrics for text-to-image models typically rely on statistical metrics which inadequately represent the real preference of humans.
no code implementations • 25 Apr 2024 • Xiang Li, Yiqun Yao, Xin Jiang, Xuezhi Fang, Chao Wang, Xinzhang Liu, Zihan Wang, Yu Zhao, Xin Wang, Yuyao Huang, Shuangyong Song, Yongxiang Li, Zheng Zhang, Bo Zhao, Aixin Sun, Yequan Wang, Zhongjiang He, Zhongyuan Wang, Xuelong Li, Tiejun Huang
Large language models (LLMs) have showcased profound capabilities in language understanding and generation, facilitating a wide array of applications.
1 code implementation • 9 Apr 2024 • Xiuqi Deng, Lu Xu, Xiyao Li, Jinkai Yu, Erpeng Xue, Zhongyuan Wang, Di Zhang, Zhaojie Liu, Guorui Zhou, Yang song, Na Mou, Shen Jiang, Han Li
In this paper, we propose an industrial multimodal recommendation framework named EM3: End-to-end training of Multimodal Model and ranking Model, which sufficiently utilizes multimodal information and allows personalized ranking tasks to directly train the core modules in the multimodal model to obtain more task-oriented content features, without overburdening resource consumption.
no code implementations • 4 Mar 2024 • Siqi Fan, Xin Jiang, Xiang Li, Xuying Meng, Peng Han, Shuo Shang, Aixin Sun, Yequan Wang, Zhongyuan Wang
That is, not all layers of LLMs are necessary during inference.
1 code implementation • 6 Jan 2024 • Yaojia LV, Haojie Pan, Zekun Wang, Jiafeng Liang, Yuanxing Liu, Ruiji Fu, Ming Liu, Zhongyuan Wang, Bing Qin
Cognitive dynamics are pivotal to advance human understanding of the world.
1 code implementation • 20 Dec 2023 • Tao Zhang, Xingye Tian, Yikang Zhou, Shunping Ji, Xuebo Wang, Xin Tao, Yuan Zhang, Pengfei Wan, Zhongyuan Wang, Yu Wu
We present the \textbf{D}ecoupled \textbf{VI}deo \textbf{S}egmentation (DVIS) framework, a novel approach for the challenging task of universal video segmentation, including video instance segmentation (VIS), video semantic segmentation (VSS), and video panoptic segmentation (VPS).
Ranked #1 on Video Semantic Segmentation on VSPW
1 code implementation • 8 Dec 2023 • Haojie Pan, Zepeng Zhai, Hao Yuan, Yaojia LV, Ruiji Fu, Ming Liu, Zhongyuan Wang, Bing Qin
Driven by curiosity, humans have continually sought to explore and understand the world around them, leading to the invention of various tools to satiate this inquisitiveness.
1 code implementation • 27 Nov 2023 • Qi Fan, Xin Tao, Lei Ke, Mingqiao Ye, Yuan Zhang, Pengfei Wan, Zhongyuan Wang, Yu-Wing Tai, Chi-Keung Tang
Thus, our solution, termed Stable-SAM, offers several advantages: 1) improved SAM's segmentation stability across a wide range of prompt qualities, while 2) retaining SAM's powerful promptable segmentation efficiency and generality, with 3) minimal learnable parameters (0. 08 M) and fast adaptation (by 1 training epoch).
1 code implementation • 24 Nov 2023 • Weijia Wu, Zhuang Li, Yefei He, Mike Zheng Shou, Chunhua Shen, Lele Cheng, Yan Li, Tingting Gao, Di Zhang, Zhongyuan Wang
In this paper, we introduce an information-enriched diffusion model for paragraph-to-image generation task, termed ParaDiffusion, which delves into the transference of the extensive semantic comprehension capabilities of large language models to the task of image generation.
no code implementations • 16 Nov 2023 • Ming Chen, Yan Zhou, Weihua Jian, Pengfei Wan, Zhongyuan Wang
Though significant progress in human pose and shape recovery from monocular RGB images has been made in recent years, obtaining 3D human motion with high accuracy and temporal consistency from videos remains challenging.
Ranked #3 on 3D Human Pose Estimation on 3DPW
no code implementations • 14 Nov 2023 • Lei Lin, Jiayi Fu, Pengli Liu, Qingyang Li, Yan Gong, Junchen Wan, Fuzheng Zhang, Zhongyuan Wang, Di Zhang, Kun Gai
Although chain-of-thought (CoT) prompting combined with language models has achieved encouraging results on complex reasoning tasks, the naive greedy decoding used in CoT prompting usually causes the repetitiveness and local optimality.
no code implementations • 9 Nov 2023 • Cheng Yang, Rui Xu, Ye Guo, Peixiang Huang, Yiru Chen, Wenkui Ding, Zhongyuan Wang, Hong Zhou
Further, we design two pre-training tasks named object position regression (OPR) and spatial relation classification (SRC) to learn to reconstruct the spatial relation graph respectively.
no code implementations • 23 Oct 2023 • Yulan Hu, Sheng Ouyang, Jingyu Liu, Ge Chen, Zhirui Yang, Junchen Wan, Fuzheng Zhang, Zhongyuan Wang, Yong liu
Thus, we propose GraphRank, a simple yet efficient graph contrastive learning method that addresses the problem of false negative samples by redefining the concept of negative samples to a certain extent, thereby avoiding the issue of false negative samples.
no code implementations • 11 Oct 2023 • Jiayi Fu, Lei Lin, Xiaoyang Gao, Pengli Liu, Zhengzong Chen, Zhirui Yang, ShengNan Zhang, Xue Zheng, Yan Li, Yuliang Liu, Xucheng Ye, Yiqiao Liao, Chao Liao, Bin Chen, Chengru Song, Junchen Wan, Zijia Lin, Fuzheng Zhang, Zhongyuan Wang, Di Zhang, Kun Gai
Recent advancements in large language models (LLMs) have demonstrated remarkable abilities in handling a variety of natural language processing (NLP) downstream tasks, even on mathematical tasks requiring multi-step reasoning.
Ranked #93 on Arithmetic Reasoning on GSM8K (using extra training data)
no code implementations • 19 Sep 2023 • Hongyang Chen, Yuhong Yang, Zhongyuan Wang, Weiping tu, Haojun Ai, Song Lin
This study explores how sentence types affect the Lombard effect and intelligibility enhancement, focusing on comparisons between natural and grid sentences.
1 code implementation • 9 Sep 2023 • Zhijie Nie, Richong Zhang, Zhongyuan Wang, Xudong Liu
Current methods for Knowledge-Based Question Answering (KBQA) usually rely on complex training techniques and model frameworks, leading to many limitations in practical applications.
no code implementations • 8 Sep 2023 • Haotian Yang, Mingwu Zheng, Wanquan Feng, Haibin Huang, Yu-Kun Lai, Pengfei Wan, Zhongyuan Wang, Chongyang Ma
Specifically, TRAvatar is trained with dynamic image sequences captured in a Light Stage under varying lighting conditions, enabling realistic relighting and real-time animation for avatars in diverse scenes.
no code implementations • 14 Mar 2023 • Chunyu Qiang, Peng Yang, Hao Che, Ying Zhang, Xiaorui Wang, Zhongyuan Wang
Cross-speaker style transfer in speech synthesis aims at transferring a style from source speaker to synthesized speech of a target speaker's timbre.
no code implementations • CVPR 2023 • Baojin Huang, Zhongyuan Wang, Jifan Yang, Jiaxin Ai, Qin Zou, Qian Wang, Dengpan Ye
Face swapping aims to replace the target face with the source face and generate the fake face that the human cannot distinguish between real and fake.
1 code implementation • CVPR 2023 • Jinsheng Xiao, Yuanxu Wu, Yunhua Chen, Shurui Wang, Zhongyuan Wang, Jiayi Ma
We find that context information from the long-term frame and temporal information from the short-term frame are two useful cues for video small object detection.
no code implementations • 13 Dec 2022 • Chunyu Qiang, Peng Yang, Hao Che, Xiaorui Wang, Zhongyuan Wang
In order to improve the style extraction ability of the reference encoder, a style invariant and contrastive data augmentation method is proposed.
no code implementations • 8 Dec 2022 • Jing Fang, Yinbo Yu, Zhongyuan Wang, Xin Ding, Ruimin Hu
Image super-resolution (SR) is a technique to recover lost high-frequency information in low-resolution (LR) images.
1 code implementation • The 33rd British Machine Vision Conference 2022 • Ji Huang, Chao Liang, Yue Zhang, Zhongyuan Wang, Chunjie Zhang
Existing RA work can be generally divided into unsupervised methods and fully-supervised methods.
no code implementations • 19 Nov 2022 • Jiaxin Deng, Dong Shen, Haojie Pan, Xiangyu Wu, Ximan Liu, Gaofeng Meng, Fan Yang, Size Li, Ruiji Fu, Zhongyuan Wang
Furthermore, based on this dataset, we propose an end-to-end model that jointly optimizes the video understanding objective with knowledge graph embedding, which can not only better inject factual knowledge into video understanding but also generate effective multi-modal entity embedding for KG.
no code implementations • 17 Nov 2022 • Chunyu Qiang, Peng Yang, Hao Che, Jinba Xiao, Xiaorui Wang, Zhongyuan Wang
In this paper we propose a simple back-translation-style data augmentation method for mandarin Chinese polyphone disambiguation, utilizing a large amount of unlabeled text data.
1 code implementation • 28 Oct 2022 • Haojie Pan, Zepeng Zhai, Yuzhou Zhang, Ruiji Fu, Ming Liu, Yangqiu Song, Zhongyuan Wang, Bing Qin
In this paper, we propose Kuaipedia, a large-scale multi-modal encyclopedia consisting of items, aspects, and short videos lined to them, which was extracted from billions of videos of Kuaishou (Kwai), a well-known short-video platform in China.
1 code implementation • 13 Oct 2022 • Xing Wu, Chaochen Gao, Zijia Lin, Zhongyuan Wang, Jizhong Han, Songlin Hu
Sparse sampling is also likely to miss important frames corresponding to some text portions, resulting in textual redundancy.
no code implementations • 10 Oct 2022 • Wanfeng Zheng, Qiang Li, Xiaoyan Guo, Pengfei Wan, Zhongyuan Wang
More specifically, our efforts consist of three parts: 1) a data-free training strategy to train latent mappers to bridge the latent space of CLIP and StyleGAN; 2) for more precise mapping, temporal relative consistency is proposed to address the knowledge distribution bias problem among different latent spaces; 3) to refine the mapped latent in s space, adaptive style mixing is also proposed.
2 code implementations • 8 Oct 2022 • Xing Wu, Chaochen Gao, Zijia Lin, Jizhong Han, Zhongyuan Wang, Songlin Hu
Contrastive learning has been extensively studied in sentence embedding learning, which assumes that the embeddings of different views of the same sentence are closer.
no code implementations • 28 Sep 2022 • Xiaohan Zou, Changqiao Wu, Lele Cheng, Zhongyuan Wang
Most existing methods in vision-language retrieval match two modalities by either comparing their global feature vectors which misses sufficient information and lacks interpretability, detecting objects in images or videos and aligning the text with fine-grained features which relies on complicated model designs, or modeling fine-grained interaction via cross-attention upon visual and textual tokens which suffers from inferior efficiency.
2 code implementations • 16 Aug 2022 • Xing Wu, Guangyuan Ma, Meng Lin, Zijia Lin, Zhongyuan Wang, Songlin Hu
Dense passage retrieval aims to retrieve the relevant passages of a query from a large corpus based on dense representations (i. e., vectors) of the query and the passages.
1 code implementation • 21 Jul 2022 • Kui Jiang, Zhongyuan Wang, Chen Chen, Zheng Wang, Laizhong Cui, Chia-Wen Lin
Convolutional neural network (CNN) and Transformer have achieved great success in multimedia applications.
1 code implementation • 18 Jul 2022 • Wejia Wu, Zhuang Li, Jiahong Li, Chunhua Shen, Hong Zhou, Size Li, Zhongyuan Wang, Ping Luo
Our contributions are three-fold: 1) CoText simultaneously address the three tasks (e. g., text detection, tracking, recognition) in a real-time end-to-end trainable framework.
no code implementations • 8 Jul 2022 • Jiaxin Ai, Zhongyuan Wang, Baojin Huang, Zhen Han
Deepfake face not only violates the privacy of personal identity, but also confuses the public and causes huge social harm.
no code implementations • 9 Jun 2022 • Weikai Yang, Xi Ye, Xingxing Zhang, Lanxi Xiao, Jiazhi Xia, Zhongyuan Wang, Jun Zhu, Hanspeter Pfister, Shixia Liu
The base learners and labeled samples (shots) in an ensemble few-shot classifier greatly affect the model performance.
1 code implementation • NeurIPS 2023 • Liang Hou, Qi Cao, Yige Yuan, Songtao Zhao, Chongyang Ma, Siyuan Pan, Pengfei Wan, Zhongyuan Wang, HuaWei Shen, Xueqi Cheng
Training generative adversarial networks (GANs) with limited data is challenging because the discriminator is prone to overfitting.
no code implementations • 30 Mar 2022 • Wanfeng Zheng, Qiang Li, Guoxin Zhang, Pengfei Wan, Zhongyuan Wang
Unpaired image-to-image translation is to translate an image from a source domain to a target domain without paired training data.
1 code implementation • CVPR 2022 • Zhuo Wang, Zezheng Wang, Zitong Yu, Weihong Deng, Jiahong Li, Tingting Gao, Zhongyuan Wang
A novel Shuffled Style Assembly Network (SSAN) is proposed to extract and reassemble different content and style features for a stylized feature space.
1 code implementation • ACL 2022 • Xing Wu, Chaochen Gao, Meng Lin, Liangjun Zang, Zhongyuan Wang, Songlin Hu
Before entering the neural network, a token is generally converted to the corresponding one-hot representation, which is a discrete distribution of the vocabulary.
1 code implementation • 30 Dec 2021 • Zhuang Li, Weijia Wu, Mike Zheng Shou, Jiahong Li, Size Li, Zhongyuan Wang, Hong Zhou
Semantic representation is of great benefit to the video text tracking(VTT) task that requires simultaneously classifying, detecting, and tracking texts in the video.
1 code implementation • 10 Dec 2021 • Chaochen Gao, Xing Wu, Peng Wang, Jue Wang, Liangjun Zang, Zhongyuan Wang, Songlin Hu
To tackle that, we propose an effective knowledge distillation framework for contrastive sentence embeddings, termed DistilCSE.
1 code implementation • 24 Nov 2021 • Zezheng Wang, Zitong Yu, Xun Wang, Yunxiao Qin, Jiahong Li, Chenxu Zhao, Zhen Lei, Xin Liu, Size Li, Zhongyuan Wang
Face anti-spoofing (FAS) plays a crucial role in securing face recognition systems.
no code implementations • 30 Oct 2021 • Yanrui Niu, Jingyao Yang, Ankang Lu, Baojin Huang, Yue Zhang, Ji Huang, Shishi Wen, Dongshu Xu, Chao Liang, Zhongyuan Wang, Jun Chen
We will make a brief introduction of the experimental methods and results of the WHU-NERCMS in the TRECVID2021 in the paper.
no code implementations • 16 Sep 2021 • Yuanzhi Wang, Tao Lu, Yanduo Zhang, Junjun Jiang, JiaMing Wang, Zhongyuan Wang, Jiayi Ma
Recently, face super-resolution (FSR) methods either feed whole face image into convolutional neural networks (CNNs) or utilize extra facial priors (e. g., facial parsing maps, facial landmarks) to focus on facial structure, thereby maintaining the consistency of the facial structure while restoring facial details.
2 code implementations • COLING 2022 • Xing Wu, Chaochen Gao, Yipeng Su, Jizhong Han, Zhongyuan Wang, Songlin Hu
Contrastive learning has been gradually applied to learn high-quality unsupervised sentence embedding.
2 code implementations • COLING 2022 • Xing Wu, Chaochen Gao, Liangjun Zang, Jizhong Han, Zhongyuan Wang, Songlin Hu
Unsup-SimCSE takes dropout as a minimal data augmentation method, and passes the same input sentence to a pre-trained Transformer encoder (with dropout turned on) twice to obtain the two corresponding embeddings to build a positive pair.
1 code implementation • 11 Jun 2021 • Xing Cheng, Hezheng Lin, Xiangyu Wu, Fan Yang, Dong Shen, Zhongyuan Wang, Nian Shi, Honglin Liu
The task of multi-label image classification is to recognize all the object labels presented in an image.
Ranked #12 on Multi-Label Classification on MS-COCO
1 code implementation • 10 Jun 2021 • Hezheng Lin, Xing Cheng, Xiangyu Wu, Fan Yang, Dong Shen, Zhongyuan Wang, Qing Song, Wei Yuan
In this paper, we propose a new attention mechanism in Transformer termed Cross Attention, which alternates attention inner the image patch instead of the whole image to capture local information and apply attention between image patches which are divided from single-channel feature maps capture global information.
no code implementations • ICCV 2021 • Peng Yi, Zhongyuan Wang, Kui Jiang, Junjun Jiang, Tao Lu, Xin Tian, Jiayi Ma
Most recent video super-resolution (SR) methods either adopt an iterative manner to deal with low-resolution (LR) frames from a temporally sliding window, or leverage the previously estimated SR output to help reconstruct the current frame recurrently.
no code implementations • ICCV 2021 • Song Liu, Haoqi Fan, Shengsheng Qian, Yiru Chen, Wenkui Ding, Zhongyuan Wang
Video-Text Retrieval has been a hot research topic with the growth of multimedia data on the internet.
1 code implementation • 19 Mar 2021 • Kui Jiang, Zhongyuan Wang, Zheng Wang, Chen Chen, Peng Yi, Tao Lu, Chia-Wen Lin
Different from existing methods tending to accomplish the relighting task directly by ignoring the fidelity and naturalness recovery, we investigate the intrinsic degradation and relight the low-light image while refining the details and color in two steps.
no code implementations • CVPR 2021 • Jiaming Li, Hongtao Xie, Jiahong Li, Zhongyuan Wang, Yongdong Zhang
Face forgery detection is raising ever-increasing interest in computer vision since facial manipulation technologies cause serious worries.
no code implementations • 15 Mar 2021 • Shenhao Cao, Qin Zou, Xiuqing Mao, Zhongyuan Wang
Detecting facial forgery images and videos is an increasingly important topic in multimedia forensics.
1 code implementation • 4 Mar 2021 • Baojin Huang, Zhongyuan Wang, Guangcheng Wang, Kui Jiang, Kangli Zeng, Zhen Han, Xin Tian, Yuhong Yang
In particular, we first collect a variety of glasses and masks as occlusion, and randomly combine the occlusion attributes (occlusion objects, textures, and colors) to achieve a large number of more realistic occlusion types.
1 code implementation • 4 Feb 2021 • Han Liu, Caixia Yuan, Xiaojie Wang, Yushu Yang, Huixing Jiang, Zhongyuan Wang
We propose a novel task, Multi-Document Driven Dialogue (MD3), in which an agent can guess the target document that the user is interested in by leading a dialogue.
no code implementations • COLING 2020 • Keqing He, Shuyu Lei, Yushu Yang, Huixing Jiang, Zhongyuan Wang
Slot filling and intent detection are two major tasks for spoken language understanding.
no code implementations • COLING 2020 • Xuemiao Zhang, Kun Zhou, Sirui Wang, Fuzheng Zhang, Zhongyuan Wang, Junfei Liu
Weakly supervised machine reading comprehension (MRC) task is practical and promising for its easily available and massive training data, but inevitablely introduces noise.
1 code implementation • EMNLP 2020 • Shaolei Wang, Zhongyuan Wang, Wanxiang Che, Ting Liu
Most existing approaches to disfluency detection heavily rely on human-annotated corpora, which is expensive to obtain in practice.
1 code implementation • 22 Oct 2020 • Tao Lu, Yuanzhi Wang, Yanduo Zhang, Yu Wang, Wei Liu, Zhongyuan Wang, Junjun Jiang
However, most of them fail to take into account the overall facial profile and fine texture details simultaneously, resulting in reduced naturalness and fidelity of the reconstructed face, and further impairing the performance of downstream tasks (e. g., face detection, facial recognition).
no code implementations • 19 Oct 2020 • Yang Yang, Junmei Hao, Canjia Li, Zili Wang, Jingang Wang, Fuzheng Zhang, Rao Fu, Peixu Hou, Gong Zhang, Zhongyuan Wang
Existing work on tip generation does not take query into consideration, which limits the impact of tips in search scenarios.
1 code implementation • 1 Oct 2020 • Zipeng Xu, Fangxiang Feng, Xiaojie Wang, Yushu Yang, Huixing Jiang, Zhongyuan Wang
In this paper, we propose an Answer-Driven Visual State Estimator (ADVSE) to impose the effects of different answers on visual states.
no code implementations • 1 Oct 2020 • Shaolei Wang, Baoxin Wang, Jiefu Gong, Zhongyuan Wang, Xiao Hu, Xingyi Duan, Zizhuo Shen, Gang Yue, Ruiji Fu, Dayong Wu, Wanxiang Che, Shijin Wang, Guoping Hu, Ting Liu
Grammatical error diagnosis is an important task in natural language processing.
no code implementations • 19 Aug 2020 • Kun Zhou, Wayne Xin Zhao, Hui Wang, Sirui Wang, Fuzheng Zhang, Zhongyuan Wang, Ji-Rong Wen
Most of the existing CRS methods focus on learning effective preference representations for users from conversation data alone.
2 code implementations • 18 Aug 2020 • Kun Zhou, Hui Wang, Wayne Xin Zhao, Yutao Zhu, Sirui Wang, Fuzheng Zhang, Zhongyuan Wang, Ji-Rong Wen
To tackle this problem, we propose the model S^3-Rec, which stands for Self-Supervised learning for Sequential Recommendation, based on the self-attentive neural architecture.
1 code implementation • 26 Mar 2020 • Yuda Qiu, Zhangyang Xiong, Kai Han, Zhongyuan Wang, Zixiang Xiong, Xiaoguang Han
To alleviate this problem, we propose a weakly supervised training approach to train our model on real face videos, based on the assumption of consistency of albedo and normal across different frames, thus bridging the gap between real and synthetic face images.
3 code implementations • CVPR 2020 • Kui Jiang, Zhongyuan Wang, Peng Yi, Chen Chen, Baojin Huang, Yimin Luo, Jiayi Ma, Junjun Jiang
In this work, we explore the multi-scale collaborative representation for rain streaks from the perspective of input image scales and hierarchical deep features in a unified framework, termed multi-scale progressive fusion network (MSPFN) for single image rain streak removal.
Ranked #6 on Single Image Deraining on Test2800
3 code implementations • 20 Mar 2020 • Zhongyuan Wang, Guangcheng Wang, Baojin Huang, Zhangyang Xiong, Qi Hong, Hao Wu, Peng Yi, Kui Jiang, Nanxi Wang, Yingjiao Pei, Heling Chen, Yu Miao, Zhibing Huang, Jinbi Liang
These datasets are freely available to industry and academia, based on which various applications on masked faces can be developed.
no code implementations • 25 Oct 2019 • Yuanhao Yue, Qin Zou, Hongkai Yu, Qian Wang, Zhongyuan Wang, Song Wang
Co-saliency detection within a single image is a common vision problem that has received little attention and has not yet been well addressed.
no code implementations • 19 May 2019 • Bowen Xing, Lejian Liao, Dandan song, Jingang Wang, Fuzheng Zhang, Zhongyuan Wang, He-Yan Huang
This paper proposes a novel variant of LSTM, termed as aspect-aware LSTM (AA-LSTM), which incorporates aspect information into LSTM cells in the context modeling stage before the attention mechanism.
Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA)
5 code implementations • 11 May 2019 • Hongwei Wang, Fuzheng Zhang, Mengdi Zhang, Jure Leskovec, Miao Zhao, Wenjie Li, Zhongyuan Wang
Here we propose Knowledge-aware Graph Neural Networks with Label Smoothness regularization (KGNN-LS) to provide better recommendations.
Ranked #1 on Recommendation Systems on Dianping-Food
1 code implementation • 26 Jun 2018 • Junjun Jiang, Jiayi Ma, Chen Chen, Zhongyuan Wang, Zhihua Cai, Lizhe Wang
(1) Unlike the traditional PCA method based on a whole image, SuperPCA takes into account the diversity in different homogeneous regions, that is, different regions should have different projections.
no code implementations • COLING 2016 • Taesung Lee, Seung-won Hwang, Zhongyuan Wang
Besides providing the relevant information, amusing users has been an important role of the web.