Search Results for author: Yan-ran Li

Found 17 papers, 7 papers with code

Detect Faces Efficiently: A Survey and Evaluations

2 code implementations3 Dec 2021 Yuantao Feng, Shiqi Yu, Hanyang Peng, Yan-ran Li, JianGuo Zhang

However, with the tremendous increase in images and videos with variations in face scale, appearance, expression, occlusion and pose, traditional face detectors are challenged to detect various "in the wild" faces.

Face Detection Face Recognition +2

iLGaCo: Incremental Learning of Gait Covariate Factors

1 code implementation31 Aug 2020 Zihao Mu, Francisco M. Castro, Manuel J. Marin-Jimenez, Nicolas Guil, Yan-ran Li, Shiqi Yu

In this paper, we propose iLGaCo, the first incremental learning approach of covariate factors for gait recognition, where the deep model can be updated with new information without re-training it from scratch by using the whole dataset.

Gait Recognition Incremental Learning

Peeking into occluded joints: A novel framework for crowd pose estimation

1 code implementation ECCV 2020 Lingteng Qiu, Xuanye Zhang, Yan-ran Li, Guanbin Li, Xiao-Jun Wu, Zixiang Xiong, Xiaoguang Han, Shuguang Cui

Although occlusion widely exists in nature and remains a fundamental challenge for pose estimation, existing heatmap-based approaches suffer serious degradation on occlusions.

Pose Estimation

PM2.5-GNN: A Domain Knowledge Enhanced Graph Neural Network For PM2.5 Forecasting

2 code implementations ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems 2020 Shuo Wang, Yan-ran Li, Jiang Zhang, Qingye Meng, Lingwei Meng, Fei Gao

When predicting PM2. 5 concentrations, it is necessary to consider complex information sources since the concentrations are influenced by various factors within a long period.

Incorporating Relevant Knowledge in Context Modeling and Response Generation

no code implementations9 Nov 2018 Yan-ran Li, Wenjie Li, Ziqiang Cao, Chengyao Chen

To sustain engaging conversation, it is critical for chatbots to make good use of relevant knowledge.

Chatbot Response Generation

Meta-path Augmented Response Generation

no code implementations2 Nov 2018 Yan-ran Li, Wenjie Li

We propose a chatbot, namely Mocha to make good use of relevant entities when generating responses.

Chatbot Response Generation

Adversarial Deep Reinforcement Learning in Portfolio Management

3 code implementations29 Aug 2018 Zhipeng Liang, Hao Chen, Junhao Zhu, Kangkang Jiang, Yan-ran Li

In this paper, we implement three state-of-art continuous reinforcement learning algorithms, Deep Deterministic Policy Gradient (DDPG), Proximal Policy Optimization (PPO) and Policy Gradient (PG)in portfolio management.

Management reinforcement-learning +1

DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset

13 code implementations IJCNLP 2017 Yan-ran Li, Hui Su, Xiaoyu Shen, Wenjie Li, Ziqiang Cao, Shuzi Niu

We develop a high-quality multi-turn dialog dataset, DailyDialog, which is intriguing in several aspects.

Maximum-Likelihood Augmented Discrete Generative Adversarial Networks

no code implementations26 Feb 2017 Tong Che, Yan-ran Li, Ruixiang Zhang, R. Devon Hjelm, Wenjie Li, Yangqiu Song, Yoshua Bengio

Despite the successes in capturing continuous distributions, the application of generative adversarial networks (GANs) to discrete settings, like natural language tasks, is rather restricted.

Mode Regularized Generative Adversarial Networks

no code implementations7 Dec 2016 Tong Che, Yan-ran Li, Athul Paul Jacob, Yoshua Bengio, Wenjie Li

Although Generative Adversarial Networks achieve state-of-the-art results on a variety of generative tasks, they are regarded as highly unstable and prone to miss modes.

AttSum: Joint Learning of Focusing and Summarization with Neural Attention

no code implementations COLING 2016 Ziqiang Cao, Wenjie Li, Sujian Li, Furu Wei, Yan-ran Li

Query relevance ranking and sentence saliency ranking are the two main tasks in extractive query-focused summarization.

Component-Enhanced Chinese Character Embeddings

no code implementations EMNLP 2015 Yan-ran Li, Wenjie Li, Fei Sun, Sujian Li

Distributed word representations are very useful for capturing semantic information and have been successfully applied in a variety of NLP tasks, especially on English.

General Classification text-classification +3

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