Search Results for author: Jing Wu

Found 40 papers, 16 papers with code

Shonan Rotation Averaging: Global Optimality by Surfing SO(p)(n)

no code implementations ECCV 2020 Frank Dellaert, David M. Rosen, Jing Wu, Robert Mahony, Luca Carlone

Shonan Rotation Averaging is a fast, simple, and elegant rotation averaging algorithm that is guaranteed to recover globally optimal solutions under mild assumptions on the measurement noise.

ReConTab: Regularized Contrastive Representation Learning for Tabular Data

no code implementations28 Oct 2023 Suiyao Chen, Jing Wu, Naira Hovakimyan, Handong Yao

In response to this challenge, we introduce ReConTab, a deep automatic representation learning framework with regularized contrastive learning.

Contrastive Learning Feature Engineering +2

Adaptive Policy with Wait-$k$ Model for Simultaneous Translation

no code implementations23 Oct 2023 Libo Zhao, Kai Fan, Wei Luo, Jing Wu, Shushu Wang, Ziqian Zeng, Zhongqiang Huang

Simultaneous machine translation (SiMT) requires a robust read/write policy in conjunction with a high-quality translation model.

Machine Translation Translation

Feature Proliferation -- the "Cancer" in StyleGAN and its Treatments

1 code implementation ICCV 2023 Shuang Song, Yuanbang Liang, Jing Wu, Yu-Kun Lai, Yipeng Qin

Thanks to our discovery of Feature Proliferation, the proposed feature rescaling method is less destructive and retains more useful image features than the truncation trick, as it is more fine-grained and works in a lower-level feature space rather than a high-level latent space.

Image Generation

Local Consensus Enhanced Siamese Network with Reciprocal Loss for Two-view Correspondence Learning

no code implementations6 Aug 2023 Linbo Wang, Jing Wu, Xianyong Fang, Zhengyi Liu, Chenjie Cao, Yanwei Fu

First, we propose a Local Feature Consensus (LFC) plugin block to augment the features of existing models.

GenCo: An Auxiliary Generator from Contrastive Learning for Enhanced Few-Shot Learning in Remote Sensing

no code implementations27 Jul 2023 Jing Wu, Naira Hovakimyan, Jennifer Hobbs

We demonstrate the effectiveness of our method in improving few-shot learning performance on two key remote sensing datasets: Agriculture-Vision and EuroSAT.

Contrastive Learning Few-Shot Learning +2

Recent Advances of Deep Robotic Affordance Learning: A Reinforcement Learning Perspective

no code implementations9 Mar 2023 Xintong Yang, Ze Ji, Jing Wu, Yu-Kun Lai

As a popular concept proposed in the field of psychology, affordance has been regarded as one of the important abilities that enable humans to understand and interact with the environment.

reinforcement-learning Reinforcement Learning (RL)

Extended Agriculture-Vision: An Extension of a Large Aerial Image Dataset for Agricultural Pattern Analysis

1 code implementation4 Mar 2023 Jing Wu, David Pichler, Daniel Marley, David Wilson, Naira Hovakimyan, Jennifer Hobbs

First, we generate and release an improved version of the Agriculture-Vision dataset (Chiu et al., 2020b) to include raw, full-field imagery for greater experimental flexibility.

Benchmarking Contrastive Learning +1

Balanced Training for Sparse GANs

1 code implementation NeurIPS 2023 Yite Wang, Jing Wu, Naira Hovakimyan, Ruoyu Sun

We also introduce a new method called balanced dynamic sparse training (ADAPT), which seeks to control the BR during GAN training to achieve a good trade-off between performance and computational cost.

Optimizing Crop Management with Reinforcement Learning and Imitation Learning

no code implementations20 Sep 2022 Ran Tao, Pan Zhao, Jing Wu, Nicolas F. Martin, Matthew T. Harrison, Carla Ferreira, Zahra Kalantari, Naira Hovakimyan

Moreover, the partial-observation management policies are directly deployable in the real world as they use readily available information.

Imitation Learning Management +2

Defense against Privacy Leakage in Federated Learning

1 code implementation13 Sep 2022 Jing Wu, Munawar Hayat, Mingyi Zhou, Mehrtash Harandi

Federated Learning (FL) provides a promising distributed learning paradigm, since it seeks to protect users privacy by not sharing their private training data.

Federated Learning

Abstract Demonstrations and Adaptive Exploration for Efficient and Stable Multi-step Sparse Reward Reinforcement Learning

1 code implementation19 Jul 2022 Xintong Yang, Ze Ji, Jing Wu, Yu-Kun Lai

Although Deep Reinforcement Learning (DRL) has been popular in many disciplines including robotics, state-of-the-art DRL algorithms still struggle to learn long-horizon, multi-step and sparse reward tasks, such as stacking several blocks given only a task-completion reward signal.

A Unified Understanding of Deep NLP Models for Text Classification

no code implementations19 Jun 2022 Zhen Li, Xiting Wang, Weikai Yang, Jing Wu, Zhengyan Zhang, Zhiyuan Liu, Maosong Sun, HUI ZHANG, Shixia Liu

The rapid development of deep natural language processing (NLP) models for text classification has led to an urgent need for a unified understanding of these models proposed individually.

text-classification Text Classification

Exploring and Exploiting Hubness Priors for High-Quality GAN Latent Sampling

1 code implementation13 Jun 2022 Yuanbang Liang, Jing Wu, Yu-Kun Lai, Yipeng Qin

Despite the extensive studies on Generative Adversarial Networks (GANs), how to reliably sample high-quality images from their latent spaces remains an under-explored topic.

Vocal Bursts Intensity Prediction

Optimizing Nitrogen Management with Deep Reinforcement Learning and Crop Simulations

no code implementations21 Apr 2022 Jing Wu, Ran Tao, Pan Zhao, Nicolas F. Martin, Naira Hovakimyan

Nitrogen (N) management is critical to sustain soil fertility and crop production while minimizing the negative environmental impact, but is challenging to optimize.

Management reinforcement-learning +1

Playing Lottery Tickets in Style Transfer Models

no code implementations25 Mar 2022 Meihao Kong, Jing Huo, Wenbin Li, Jing Wu, Yu-Kun Lai, Yang Gao

(2) Using iterative magnitude pruning, we find the matching subnetworks at 89. 2% sparsity in AdaIN and 73. 7% sparsity in SANet, which demonstrates that style transfer models can play lottery tickets too.

Style Transfer

An Open-Source Multi-Goal Reinforcement Learning Environment for Robotic Manipulation with Pybullet

2 code implementations12 May 2021 Xintong Yang, Ze Ji, Jing Wu, Yu-Kun Lai

This work re-implements the OpenAI Gym multi-goal robotic manipulation environment, originally based on the commercial Mujoco engine, onto the open-source Pybullet engine.

Multi-Goal Reinforcement Learning OpenAI Gym +1

Performance Evaluation of Adversarial Attacks: Discrepancies and Solutions

no code implementations22 Apr 2021 Jing Wu, Mingyi Zhou, Ce Zhu, Yipeng Liu, Mehrtash Harandi, Li Li

Recently, adversarial attack methods have been developed to challenge the robustness of machine learning models.

Adversarial Attack

A Survey On Universal Adversarial Attack

1 code implementation2 Mar 2021 Chaoning Zhang, Philipp Benz, Chenguo Lin, Adil Karjauv, Jing Wu, In So Kweon

The intriguing phenomenon of adversarial examples has attracted significant attention in machine learning and what might be more surprising to the community is the existence of universal adversarial perturbations (UAPs), i. e. a single perturbation to fool the target DNN for most images.

Adversarial Attack

MLVSNet: Multi-Level Voting Siamese Network for 3D Visual Tracking

1 code implementation ICCV 2021 Zhoutao Wang, Qian Xie, Yu-Kun Lai, Jing Wu, Kun Long, Jun Wang

To deal with sparsity in outdoor 3D point clouds, we propose to perform Hough voting on multi-level features to get more vote centers and retain more useful information, instead of voting only on the final level feature as in previous methods.

3D Object Detection object-detection +1

A Generalized Robotic Handwriting Learning System based on Dynamic Movement Primitives (DMPs)

1 code implementation7 Dec 2020 Qian Luo, Jing Wu, Matthew Gombolay

Learning from demonstration (LfD) is a powerful learning method to enable a robot to infer how to perform a task given one or more human demonstrations of the desired task.


Decision-based Universal Adversarial Attack

1 code implementation15 Sep 2020 Jing Wu, Mingyi Zhou, Shuaicheng Liu, Yipeng Liu, Ce Zhu

A single perturbation can pose the most natural images to be misclassified by classifiers.

Adversarial Attack

Shonan Rotation Averaging: Global Optimality by Surfing $SO(p)^n$

1 code implementation6 Aug 2020 Frank Dellaert, David M. Rosen, Jing Wu, Robert Mahony, Luca Carlone

Shonan Rotation Averaging is a fast, simple, and elegant rotation averaging algorithm that is guaranteed to recover globally optimal solutions under mild assumptions on the measurement noise.

$E^3$: Visual Exploration of Spatiotemporal Energy Demand

1 code implementation16 Jun 2020 Junqi Wu, Zhibin Niu, Jing Wu, Xiufeng Liu, Jiawan Zhang

Understanding demand-side energy behaviour is critical for making efficiency responses for energy demand management.

Human-Computer Interaction Computers and Society

Manifold Alignment for Semantically Aligned Style Transfer

1 code implementation ICCV 2021 Jing Huo, Shiyin Jin, Wenbin Li, Jing Wu, Yu-Kun Lai, Yinghuan Shi, Yang Gao

In this paper, we make a new assumption that image features from the same semantic region form a manifold and an image with multiple semantic regions follows a multi-manifold distribution.

Semantic Segmentation Style Transfer

ProbaNet: Proposal-balanced Network for Object Detection

no code implementations6 May 2020 Jing Wu, Xiang Zhang, Mingyi Zhou, Ce Zhu

Candidate object proposals generated by object detectors based on convolutional neural network (CNN) encounter easy-hard samples imbalance problem, which can affect overall performance.

object-detection Object Detection

Adversarial Imitation Attack

no code implementations28 Mar 2020 Mingyi Zhou, Jing Wu, Yipeng Liu, Xiaolin Huang, Shuaicheng Liu, Xiang Zhang, Ce Zhu

Then, the adversarial examples generated by the imitation model are utilized to fool the attacked model.

Adversarial Attack

DaST: Data-free Substitute Training for Adversarial Attacks

2 code implementations CVPR 2020 Mingyi Zhou, Jing Wu, Yipeng Liu, Shuaicheng Liu, Ce Zhu

In this paper, we propose a data-free substitute training method (DaST) to obtain substitute models for adversarial black-box attacks without the requirement of any real data.

BIG-bench Machine Learning

Analyzing the Noise Robustness of Deep Neural Networks

no code implementations26 Jan 2020 Kelei Cao, Mengchen Liu, Hang Su, Jing Wu, Jun Zhu, Shixia Liu

The key is to compare and analyze the datapaths of both the adversarial and normal examples.

Adversarial Attack

MW-GAN: Multi-Warping GAN for Caricature Generation with Multi-Style Geometric Exaggeration

no code implementations7 Jan 2020 Haodi Hou, Jing Huo, Jing Wu, Yu-Kun Lai, Yang Gao

Given an input face photo, the goal of caricature generation is to produce stylized, exaggerated caricatures that share the same identity as the photo.

Caricature Style Transfer

Joint Power and Coverage Control of Massive UAVs in Post-Disaster Emergency Networks: An Aggregative Game-Theoretic Learning Approach

no code implementations19 Jul 2019 Jing Wu, Qimei Chen, Hao Jiang, Haozhao Wang, Yulai Xie, Wenzheng Xu, Pan Zhou, Zichuan Xu, Lixing Chen, Beibei Li, Xiumin Wang, Dapeng Oliver Wu

In the context of fifth-generation (5G)/beyond-5G (B5G) wireless communications, post-disaster emergency networks have recently gained increasing attention and interest.

Rigid Point Registration with Expectation Conditional Maximization

no code implementations7 Mar 2018 Jing Wu

This paper addresses the issue of matching rigid 3D object points with 2D image points through point registration based on maximum likelihood principle in computer simulated images.


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