Search Results for author: Jiang Li

Found 16 papers, 4 papers with code

Simple Model Also Works: A Novel Emotion Recognition Network in Textual Conversation Based on Curriculum Learning Strategy

no code implementations12 Aug 2023 Jiang Li, XiaoPing Wang, Yingjian Liu, Qing Zhou, Zhigang Zeng

To simulate the way humans learn curriculum from easy to hard, we apply the idea of CL to the ERC task to progressively optimize the network parameters of ERNetCL.

Emotion Recognition in Conversation

CFN-ESA: A Cross-Modal Fusion Network with Emotion-Shift Awareness for Dialogue Emotion Recognition

no code implementations28 Jul 2023 Jiang Li, Yingjian Liu, XiaoPing Wang, Zhigang Zeng

RUME is applied to extract conversation-level contextual emotional cues while pulling together the data distributions between modalities; ACME is utilized to perform multimodal interaction centered on textual modality; LESM is used to model emotion shift and capture related information, thereby guide the learning of the main task.

Emotion Recognition in Conversation Multimodal Emotion Recognition

TransERR: Translation-based Knowledge Graph Completion via Efficient Relation Rotation

1 code implementation26 Jun 2023 Jiang Li, Xiangdong Su

This paper presents translation-based knowledge graph completion method via efficient relation rotation (TransERR), a straightforward yet effective alternative to traditional translation-based knowledge graph completion models.


Towards Complex Real-World Safety Factory Inspection: A High-Quality Dataset for Safety Clothing and Helmet Detection

no code implementations3 Jun 2023 Fusheng Yu, XiaoPing Wang, Jiang Li, Shaojin Wu, Junjie Zhang, Zhigang Zeng

However, limited availability of high-quality datasets has hindered the development of deep learning methods for safety clothing and helmet detection.

object-detection Object Detection

SimHaze: game engine simulated data for real-world dehazing

no code implementations25 May 2023 Zhengyang Lou, Huan Xu, Fangzhou Mu, Yanli Liu, XiaoYu Zhang, Liang Shang, Jiang Li, Bochen Guan, Yin Li, Yu Hen Hu

Using a modern game engine, our approach renders crisp clean images and their precise depth maps, based on which high-quality hazy images can be synthesized for training dehazing models.

Depth Estimation Image Dehazing +1

The Devil is in the Upsampling: Architectural Decisions Made Simpler for Denoising with Deep Image Prior

2 code implementations ICCV 2023 Yilin Liu, Jiang Li, Yunkui Pang, Dong Nie, Pew-Thian Yap

Existing methods mostly handcraft or search for the architecture from a large design space, due to the lack of understanding on how the architectural choice corresponds to the image.

Image Denoising

InferEM: Inferring the Speaker's Intention for Empathetic Dialogue Generation

no code implementations13 Dec 2022 Guoqing Lv, Jiang Li, XiaoPing Wang, Zhigang Zeng

We separately encode the last utterance and fuse it with the entire dialogue through the multi-head attention based intention fusion module to capture the speaker's intention.

Dialogue Generation Empathetic Response Generation +2

SciEv: Finding Scientific Evidence Papers for Scientific News

no code implementations30 Apr 2022 Md Reshad Ul Hoque, Jiang Li, Jian Wu

To our best knowledge, this is the first dataset of this kind.

JIZHI: A Fast and Cost-Effective Model-As-A-Service System for Web-Scale Online Inference at Baidu

1 code implementation3 Jun 2021 Hao liu, Qian Gao, Jiang Li, Xiaochao Liao, Hao Xiong, Guangxing Chen, Wenlin Wang, Guobao Yang, Zhiwei Zha, daxiang dong, Dejing Dou, Haoyi Xiong

In this work, we present JIZHI - a Model-as-a-Service system - that per second handles hundreds of millions of online inference requests to huge deep models with more than trillions of sparse parameters, for over twenty real-time recommendation services at Baidu, Inc.

Recommendation Systems

AUSN: Approximately Uniform Quantization by Adaptively Superimposing Non-uniform Distribution for Deep Neural Networks

no code implementations8 Jul 2020 Liu Fangxin, Zhao Wenbo, Wang Yanzhi, Dai Changzhi, Jiang Li

Theoretical analysis~(see Appendix A) and accuracy evaluation on various DNN models of different tasks show the effectiveness and generalization of AUSN.

Image Classification Quantization

Deep Models for Engagement Assessment With Scarce Label Information

no code implementations21 Oct 2016 Feng Li, Guangfan Zhang, Wei Wang, Roger Xu, Tom Schnell, Jonathan Wen, Frederic McKenzie, Jiang Li

We compared performances of the new data representations with the original EEG features for engagement assessment.

EEG Electroencephalogram (EEG)

Cannot find the paper you are looking for? You can Submit a new open access paper.