Search Results for author: Jingjing Li

Found 51 papers, 22 papers with code

GSMFlow: Generation Shifts Mitigating Flow for Generalized Zero-Shot Learning

no code implementations5 Jul 2022 Zhi Chen, Yadan Luo, Sen Wang, Jingjing Li, Zi Huang

To address this issue, we propose a novel flow-based generative framework that consists of multiple conditional affine coupling layers for learning unseen data generation.

Generalized Zero-Shot Learning

A Unified Strategy for Multilingual Grammatical Error Correction with Pre-trained Cross-Lingual Language Model

no code implementations26 Jan 2022 Xin Sun, Tao Ge, Shuming Ma, Jingjing Li, Furu Wei, Houfeng Wang

Synthetic data construction of Grammatical Error Correction (GEC) for non-English languages relies heavily on human-designed and language-specific rules, which produce limited error-corrected patterns.

Grammatical Error Correction Language Modelling +1

Exploring Denoised Cross-Video Contrast for Weakly-Supervised Temporal Action Localization

no code implementations CVPR 2022 Jingjing Li, Tianyu Yang, Wei Ji, Jue Wang, Li Cheng

Inspired by recent success in unsupervised contrastive representation learning, we propose a novel denoised cross-video contrastive algorithm, aiming to enhance the feature discrimination ability of video snippets for accurate temporal action localization in the weakly-supervised setting.

Contrastive Learning Denoising +4

Distinguishing Unseen From Seen for Generalized Zero-Shot Learning

no code implementations CVPR 2022 Hongzu Su, Jingjing Li, Zhi Chen, Lei Zhu, Ke Lu

In this paper, we present a novel method which leverages both visual and semantic modalities to distinguish seen and unseen categories.

Generalized Zero-Shot Learning

Region Semantically Aligned Network for Zero-Shot Learning

no code implementations14 Oct 2021 Ziyang Wang, Yunhao Gou, Jingjing Li, Yu Zhang, Yang Yang

Zero-shot learning (ZSL) aims to recognize unseen classes based on the knowledge of seen classes.

Transfer Learning Zero-Shot Learning

Domain Adaptive Semantic Segmentation without Source Data

1 code implementation13 Oct 2021 Fuming You, Jingjing Li, Lei Zhu, Ke Lu, Zhi Chen, Zi Huang

To address these problems, we investigate domain adaptive semantic segmentation without source data, which assumes that the model is pre-trained on the source domain, and then adapting to the target domain without accessing source data anymore.

Semantic Segmentation

Test-time Batch Statistics Calibration for Covariate Shift

no code implementations6 Oct 2021 Fuming You, Jingjing Li, Zhou Zhao

An previous solution is test time normalization, which substitutes the source statistics in BN layers with the target batch statistics.

Domain Generalization Image Classification +1

Adversarial Energy Disaggregation for Non-intrusive Load Monitoring

no code implementations2 Aug 2021 Zhekai Du, Jingjing Li, Lei Zhu, Ke Lu, Heng Tao Shen

Energy disaggregation, also known as non-intrusive load monitoring (NILM), challenges the problem of separating the whole-home electricity usage into appliance-specific individual consumptions, which is a typical application of data analysis.

Non-Intrusive Load Monitoring

Spectrum Gaussian Processes Based On Tunable Basis Functions

no code implementations14 Jul 2021 Wenqi Fang, Guanlin Wu, Jingjing Li, Zheng Wang, Jiang Cao, Yang Ping

Spectral approximation and variational inducing learning for the Gaussian process are two popular methods to reduce computational complexity.

Gaussian Processes

Mitigating Generation Shifts for Generalized Zero-Shot Learning

1 code implementation7 Jul 2021 Zhi Chen, Yadan Luo, Sen Wang, Ruihong Qiu, Jingjing Li, Zi Huang

Generalized Zero-Shot Learning (GZSL) is the task of leveraging semantic information (e. g., attributes) to recognize the seen and unseen samples, where unseen classes are not observable during training.

Generalized Zero-Shot Learning

A convolutional neural network for prestack fracture detection

no code implementations3 Jul 2021 Zhenyu Yuan, Yuxin Jiang, Jingjing Li, Handong Huang

From prestack seismic gathers, anisotropic analysis and inversion were commonly applied to characterize the dominant orientations and relative intensities of fractures.

Exploiting Cross-Session Information for Session-based Recommendation with Graph Neural Networks

no code implementations2 Jul 2021 Ruihong Qiu, Zi Huang, Jingjing Li, Hongzhi Yin

Different from the traditional recommender system, the session-based recommender system introduces the concept of the session, i. e., a sequence of interactions between a user and multiple items within a period, to preserve the user's recent interest.

Representation Learning Session-Based Recommendations

Multi-Stage Aggregated Transformer Network for Temporal Language Localization in Videos

no code implementations CVPR 2021 Mingxing Zhang, Yang Yang, Xinghan Chen, Yanli Ji, Xing Xu, Jingjing Li, Heng Tao Shen

Then for a moment candidate, we concatenate the starting/middle/ending representations of its starting/middle/ending elements respectively to form the final moment representation.

Calibrated RGB-D Salient Object Detection

1 code implementation CVPR 2021 Wei Ji, Jingjing Li, Shuang Yu, Miao Zhang, Yongri Piao, Shunyu Yao, Qi Bi, Kai Ma, Yefeng Zheng, Huchuan Lu, Li Cheng

Complex backgrounds and similar appearances between objects and their surroundings are generally recognized as challenging scenarios in Salient Object Detection (SOD).

object-detection RGB-D Salient Object Detection +1

Dual MINE-based Neural Secure Communications under Gaussian Wiretap Channel

no code implementations25 Feb 2021 Jingjing Li, Zhuo Sun, Lei Zhang, Hongyu Zhu

The security constraints of this method is constructed only with the input and output signal samples of the legal and eavesdropper channels and benefit that training the encoder is completely independent of the decoder.

Open-Retrieval Conversational Machine Reading

1 code implementation17 Feb 2021 Yifan Gao, Jingjing Li, Chien-Sheng Wu, Michael R. Lyu, Irwin King

On our created OR-ShARC dataset, MUDERN achieves the state-of-the-art performance, outperforming existing single-passage conversational machine reading models as well as a new multi-passage conversational machine reading baseline by a large margin.

Discourse Segmentation Reading Comprehension

Semantics Disentangling for Generalized Zero-Shot Learning

1 code implementation ICCV 2021 Zhi Chen, Yadan Luo, Ruihong Qiu, Sen Wang, Zi Huang, Jingjing Li, Zheng Zhang

Generalized zero-shot learning (GZSL) aims to classify samples under the assumption that some classes are not observable during training.

Generalized Zero-Shot Learning

Entropy-Based Uncertainty Calibration for Generalized Zero-Shot Learning

no code implementations9 Jan 2021 Zhi Chen, Zi Huang, Jingjing Li, Zheng Zhang

To address these issues, in this paper, we propose a novel framework that leverages dual variational autoencoders with a triplet loss to learn discriminative latent features and applies the entropy-based calibration to minimize the uncertainty in the overlapped area between the seen and unseen classes.

Generalized Zero-Shot Learning

BV-Person: A Large-Scale Dataset for Bird-View Person Re-Identification

no code implementations ICCV 2021 Cheng Yan, Guansong Pang, Lei Wang, Jile Jiao, Xuetao Feng, Chunhua Shen, Jingjing Li

In this work we introduce a new ReID task, bird-view person ReID, which aims at searching for a person in a gallery of horizontal-view images with the query images taken from a bird's-eye view, i. e., an elevated view of an object from above.

Person Re-Identification

Deep Pairwise Hashing for Cold-start Recommendation

no code implementations2 Nov 2020 Yan Zhang, Ivor W. Tsang, Hongzhi Yin, Guowu Yang, Defu Lian, Jingjing Li

Specifically, we first pre-train robust item representation from item content data by a Denoising Auto-encoder instead of other deterministic deep learning frameworks; then we finetune the entire framework by adding a pairwise loss objective with discrete constraints; moreover, DPH aims to minimize a pairwise ranking loss that is consistent with the ultimate goal of recommendation.


Towards Fair Knowledge Transfer for Imbalanced Domain Adaptation

no code implementations23 Oct 2020 Taotao Jing, Bingrong Xu, Jingjing Li, Zhengming Ding

Such three strategies are formulated into a unified framework to address the fairness issue and domain shift challenge.

Domain Adaptation Fairness

Discern: Discourse-Aware Entailment Reasoning Network for Conversational Machine Reading

1 code implementation EMNLP 2020 Yifan Gao, Chien-Sheng Wu, Jingjing Li, Shafiq Joty, Steven C. H. Hoi, Caiming Xiong, Irwin King, Michael R. Lyu

Based on the learned EDU and entailment representations, we either reply to the user our final decision "yes/no/irrelevant" of the initial question, or generate a follow-up question to inquiry more information.

Decision Making Discourse Segmentation +2

Rethinking Generative Zero-Shot Learning: An Ensemble Learning Perspective for Recognising Visual Patches

no code implementations27 Jul 2020 Zhi Chen, Sen Wang, Jingjing Li, Zi Huang

A voting strategy averages the probability distributions output from the classifiers and, given that some patches are more discriminative than others, a discrimination-based attention mechanism helps to weight each patch accordingly.

Ensemble Learning Fine-Grained Image Classification +1

Dual-level Semantic Transfer Deep Hashing for Efficient Social Image Retrieval

1 code implementation10 Jun 2020 Lei Zhu, Hui Cui, Zhiyong Cheng, Jingjing Li, Zheng Zhang

Specifically, we design a complementary dual-level semantic transfer mechanism to efficiently discover the potential semantics of tags and seamlessly transfer them into binary hash codes.

Image Retrieval Representation Learning

Hybrid-DNNs: Hybrid Deep Neural Networks for Mixed Inputs

no code implementations18 May 2020 Zhenyu Yuan, Yuxin Jiang, Jingjing Li, Handong Huang

Regarding as a combination of feature learning and target learning, the new proposed networks provide great capacity in high-hierarchy feature extraction and in-depth data mining.

Multi-Feature Discrete Collaborative Filtering for Fast Cold-start Recommendation

no code implementations24 Mar 2020 Yang Xu, Lei Zhu, Zhiyong Cheng, Jingjing Li, Jiande Sun

Additionally, we develop a fast discrete optimization algorithm to directly compute the binary hash codes with simple operations.

Collaborative Filtering Quantization

Memory-oriented Decoder for Light Field Salient Object Detection

1 code implementation NeurIPS 2019 Miao Zhang, Jingjing Li, Ji Wei, Yongri Piao, Huchuan Lu

In this paper, we present a deep-learning-based method where a novel memory-oriented decoder is tailored for light field saliency detection.

object-detection RGB Salient Object Detection +2

Rethinking the Item Order in Session-based Recommendation with Graph Neural Networks

1 code implementation27 Nov 2019 Ruihong Qiu, Jingjing Li, Zi Huang, Hongzhi Yin

In this paper, therefore, we study the item transition pattern by constructing a session graph and propose a novel model which collaboratively considers the sequence order and the latent order in the session graph for a session-based recommender system.

Graph Classification Session-Based Recommendations

Improving Question Generation With to the Point Context

no code implementations IJCNLP 2019 Jingjing Li, Yifan Gao, Lidong Bing, Irwin King, Michael R. Lyu

Question generation (QG) is the task of generating a question from a reference sentence and a specified answer within the sentence.

Question Generation

CANZSL: Cycle-Consistent Adversarial Networks for Zero-Shot Learning from Natural Language

no code implementations21 Sep 2019 Zhi Chen, Jingjing Li, Yadan Luo, Zi Huang, Yang Yang

Thus, a multi-modal cycle-consistency loss between the synthesized semantic representations and the ground truth can be learned and leveraged to enforce the generated semantic features to approximate to the real distribution in semantic space.

Zero-Shot Learning

Cycle-consistent Conditional Adversarial Transfer Networks

1 code implementation17 Sep 2019 Jingjing Li, Erpeng Chen, Zhengming Ding, Lei Zhu, Ke Lu, Zi Huang

Domain adaptation investigates the problem of cross-domain knowledge transfer where the labeled source domain and unlabeled target domain have distinctive data distributions.

Domain Adaptation

Alleviating Feature Confusion for Generative Zero-shot Learning

1 code implementation17 Sep 2019 Jingjing Li, Mengmeng Jing, Ke Lu, Lei Zhu, Yang Yang, Zi Huang

An inevitable issue of such a paradigm is that the synthesized unseen features are prone to seen references and incapable to reflect the novelty and diversity of real unseen instances.

Generalized Zero-Shot Learning

SpatialNLI: A Spatial Domain Natural Language Interface to Databases Using Spatial Comprehension

no code implementations28 Aug 2019 Jingjing Li, Wenlu Wang, Wei-Shinn Ku, Yingtao Tian, Haixun Wang

A natural language interface (NLI) to databases is an interface that translates a natural language question to a structured query that is executable by database management systems (DBMS).

Management Reading Comprehension

Curiosity-driven Reinforcement Learning for Diverse Visual Paragraph Generation

no code implementations1 Aug 2019 Yadan Luo, Zi Huang, Zheng Zhang, Ziwei Wang, Jingjing Li, Yang Yang

Visual paragraph generation aims to automatically describe a given image from different perspectives and organize sentences in a coherent way.

Decision Making Imitation Learning +1

Agile Domain Adaptation

no code implementations11 Jul 2019 Jingjing Li, Mengmeng Jing, Yue Xie, Ke Lu, Zi Huang

Because of the distribution shifts, different target samples have distinct degrees of difficulty in adaptation.

Domain Adaptation

From Zero-Shot Learning to Cold-Start Recommendation

1 code implementation20 Jun 2019 Jingjing Li, Mengmeng Jing, Ke Lu, Lei Zhu, Yang Yang, Zi Huang

This work, for the first time, formulates CSR as a ZSL problem, and a tailor-made ZSL method is proposed to handle CSR.

Recommendation Systems Zero-Shot Learning

A Fusion Adversarial Underwater Image Enhancement Network with a Public Test Dataset

no code implementations17 Jun 2019 Hanyu Li, Jingjing Li, Wei Wang

Underwater image enhancement algorithms have attracted much attention in underwater vision task.

Image Enhancement

Coupled VAE: Improved Accuracy and Robustness of a Variational Autoencoder

1 code implementation3 Jun 2019 Shichen Cao, Jingjing Li, Kenric P. Nelson, Mark A. Kon

We analyze the histogram of the likelihoods of the input images using the generalized mean, which measures the model's accuracy as a function of the relative risk.

Adaptive Collaborative Similarity Learning for Unsupervised Multi-view Feature Selection

no code implementations25 Apr 2019 Xiao Dong, Lei Zhu, Xuemeng Song, Jingjing Li, Zhiyong Cheng

We propose to dynamically learn the collaborative similarity structure, and further integrate it with the ultimate feature selection into a unified framework.

feature selection

Discrete Optimal Graph Clustering

1 code implementation25 Apr 2019 Yudong Han, Lei Zhu, Zhiyong Cheng, Jingjing Li, Xiaobai Liu

2) the relaxing process of cluster labels may cause significant information loss.

Graph Clustering graph construction

Leveraging the Invariant Side of Generative Zero-Shot Learning

2 code implementations CVPR 2019 Jingjing Li, Mengmeng Jin, Ke Lu, Zhengming Ding, Lei Zhu, Zi Huang

In this paper, we take the advantage of generative adversarial networks (GANs) and propose a novel method, named leveraging invariant side GAN (LisGAN), which can directly generate the unseen features from random noises which are conditioned by the semantic descriptions.

Generalized Zero-Shot Learning

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