Search Results for author: Hao Zhu

Found 67 papers, 31 papers with code

Migrating Face Swap to Mobile Devices: A lightweight Framework and A Supervised Training Solution

1 code implementation13 Apr 2022 Haiming Yu, Hao Zhu, Xiangju Lu, Junhui Liu

In this work, we propose MobileFSGAN, a novel lightweight GAN for face swap that can run on mobile devices with much fewer parameters while achieving competitive performance.

Image Generation

Epipolar Focus Spectrum: A Novel Light Field Representation and Application in Dense-view Reconstruction

no code implementations1 Apr 2022 Yaning Li, Xue Wang, Hao Zhu, Guoqing Zhou, Qing Wang

Existing light field representations, such as epipolar plane image (EPI) and sub-aperture images, do not consider the structural characteristics across the views, so they usually require additional disparity and spatial structure cues for follow-up tasks.

Ensemble Spectral Prediction (ESP) Model for Metabolite Annotation

no code implementations25 Mar 2022 Xinmeng Li, Hao Zhu, Li-Ping Liu, Soha Hassoun

We show that annotation performance, for ESP and other models, is a strong function of the number of molecules in the candidate set and their similarity to the target molecule.

SSGCNet: A Sparse Spectra Graph Convolutional Network for Epileptic EEG Signal Classification

no code implementations24 Mar 2022 Jialin Wang, Rui Gao, Haotian Zheng, Hao Zhu, C. -J. Richard Shi

Compared with the existing literature, our WNFG of EEG signals achieves up to 10 times of redundant edge reduction, and our approach achieves up to 97 times of model pruning without loss of classification accuracy.

Classification EEG

Graph-adaptive Rectified Linear Unit for Graph Neural Networks

no code implementations13 Feb 2022 Yifei Zhang, Hao Zhu, Ziqiao Meng, Piotr Koniusz, Irwin King

However, in the updating stage, all nodes share the same updating function.

Contrastive Laplacian Eigenmaps

1 code implementation NeurIPS 2021 Hao Zhu, Ke Sun, Piotr Koniusz

Starting from a GAN-inspired contrastive formulation, we show that the Jensen-Shannon divergence underlying many contrastive graph embedding models fails under disjoint positive and negative distributions, which may naturally emerge during sampling in the contrastive setting.

Contrastive Learning Graph Embedding

Detailed Facial Geometry Recovery from Multi-View Images by Learning an Implicit Function

1 code implementation4 Jan 2022 Yunze Xiao, Hao Zhu, Haotian Yang, Zhengyu Diao, Xiangju Lu, Xun Cao

By fitting a 3D morphable model from multi-view images, the features of multiple images are extracted and aggregated in the mesh-attached UV space, which makes the implicit function more effective in recovering detailed facial shape.

MoFaNeRF: Morphable Facial Neural Radiance Field

1 code implementation4 Dec 2021 Yiyu Zhuang, Hao Zhu, Xusen Sun, Xun Cao

Specifically, MoFaNeRF takes the coded facial shape, expression and appearance along with space coordinate and view direction as input to an MLP, and outputs the radiance of the space point for photo-realistic image synthesis.

Image Generation Novel View Synthesis

Appliance Level Short-term Load Forecasting via Recurrent Neural Network

no code implementations23 Nov 2021 Yuqi Zhou, Arun Sukumaran Nair, David Ganger, Abhinandan Tripathi, Chaitanya Baone, Hao Zhu

Accurate load forecasting is critical for electricity market operations and other real-time decision-making tasks in power systems.

Decision Making Load Forecasting

Scalable Learning for Optimal Load Shedding Under Power Grid Emergency Operations

no code implementations23 Nov 2021 Yuqi Zhou, Jeehyun Park, Hao Zhu

Effective and timely responses to unexpected contingencies are crucial for enhancing the resilience of power grids.

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FaceScape: 3D Facial Dataset and Benchmark for Single-View 3D Face Reconstruction

1 code implementation1 Nov 2021 Hao Zhu, Haotian Yang, Longwei Guo, Yidi Zhang, Yanru Wang, Mingkai Huang, Qiu Shen, Ruigang Yang, Xun Cao

By training on FaceScape data, a novel algorithm is proposed to predict elaborate riggable 3D face models from a single image input.

3D Face Reconstruction 3D Reconstruction

On the Sample Complexity of Decentralized Linear Quadratic Regulator with Partially Nested Information Structure

no code implementations14 Oct 2021 Lintao Ye, Hao Zhu, Vijay Gupta

We study the problem of control policy design for decentralized state-feedback linear quadratic control with a partially nested information structure, when the system model is unknown.

Risk-Aware Learning for Scalable Voltage Optimization in Distribution Grids

1 code implementation4 Oct 2021 Shanny Lin, Shaohui Liu, Hao Zhu

Real-time coordination of distributed energy resources (DERs) is crucial for regulating the voltage profile in distribution grids.

Decision Making

Few-shot graph link prediction with domain adaptation

no code implementations29 Sep 2021 Hao Zhu, Mahashweta Das, Mangesh Bendre, Fei Wang, Hao Yang, Soha Hassoun

In this work, we propose an adversarial training based modification to the current state-of-the-arts link prediction method to solve this problem.

Domain Adaptation Few-Shot Learning +1

Dependency Induction Through the Lens of Visual Perception

1 code implementation CoNLL (EMNLP) 2021 Ruisi Su, Shruti Rijhwani, Hao Zhu, Junxian He, Xinyu Wang, Yonatan Bisk, Graham Neubig

Our experiments find that concreteness is a strong indicator for learning dependency grammars, improving the direct attachment score (DAS) by over 50\% as compared to state-of-the-art models trained on pure text.

Constituency Grammar Induction Dependency Parsing

REFINE: Random RangE FInder for Network Embedding

no code implementations24 Aug 2021 Hao Zhu, Piotr Koniusz

Moreover, we design a simple but efficient spectral filter for network enhancement to obtain higher-order information for node representation.

Network Embedding Node Classification

CIGLI: Conditional Image Generation from Language & Image

1 code implementation20 Aug 2021 Xiaopeng Lu, Lynnette Ng, Jared Fernandez, Hao Zhu

Instead of generating an image based on text as in text-image generation, this task requires the generation of an image from a textual description and an image prompt.

Conditional Image Generation

Data-driven Modeling for Distribution Grids Under Partial Observability

no code implementations18 Aug 2021 Shanny Lin, Hao Zhu

Accurately modeling power distribution grids is crucial for designing effective monitoring and decision making algorithms.

Decision Making

Efficient Representation for Electric Vehicle Charging Station Operations using Reinforcement Learning

no code implementations7 Aug 2021 Kyung-bin Kwon, Hao Zhu

Effectively operating electrical vehicle charging station (EVCS) is crucial for enabling the rapid transition of electrified transportation.

reinforcement-learning

Detailed Avatar Recovery from Single Image

no code implementations6 Aug 2021 Hao Zhu, Xinxin Zuo, Haotian Yang, Sen Wang, Xun Cao, Ruigang Yang

In this paper, we propose a novel learning-based framework that combines the robustness of the parametric model with the flexibility of free-form 3D deformation.

Graph Convolutional Network with Generalized Factorized Bilinear Aggregation

no code implementations24 Jul 2021 Hao Zhu, Piotr Koniusz

Although Graph Convolutional Networks (GCNs) have demonstrated their power in various applications, the graph convolutional layers, as the most important component of GCN, are still using linear transformations and a simple pooling step.

Text Classification

Few-shot Language Coordination by Modeling Theory of Mind

no code implementations12 Jul 2021 Hao Zhu, Graham Neubig, Yonatan Bisk

Positive results from our experiments hint at the importance of explicitly modeling communication as a socio-pragmatic progress.

Graph Neural Networks for Learning Real-Time Prices in Electricity Market

1 code implementation19 Jun 2021 Shaohui Liu, Chengyang Wu, Hao Zhu

Solving the optimal power flow (OPF) problem in real-time electricity market improves the efficiency and reliability in the integration of low-carbon energy resources into the power grids.

Inferring power system dynamics from synchrophasor data using Gaussian processes

no code implementations26 May 2021 Mana Jalali, Vassilis Kekatos, Siddharth Bhela, Hao Zhu, Virgilio Centeno

Synchrophasor data provide unprecedented opportunities for inferring power system dynamics, such as estimating voltage angles, frequencies, and accelerations along with power injection at all buses.

Gaussian Processes

A Dynamic Response Recovery Framework Using Ambient Synchrophasor Data

1 code implementation12 Apr 2021 Shaohui Liu, Hao Zhu, Vassilis Kekatos

Wide-area dynamic studies are of paramount importance to ensure the stability and reliability of power grids.

Enhancing the Spatio-temporal Observability of Grid-Edge Resources in Distribution Grids

no code implementations15 Feb 2021 Shanny Lin, Hao Zhu

The load recovery solutions can be utilized to identify the EV charging events at each load node and to infer the total behind-the-meter PV output.

Deep Anti-aliasing of Whole Focal Stack Using Slice Spectrum

no code implementations23 Jan 2021 Yaning Li, Xue Wang, Hao Zhu, Guoqing Zhou, Qing Wang

Based on these two observations, we propose a learning-based FSS reconstruction approach for one-time aliasing removing over the whole focal stack.

Depth Estimation

Simple Spectral Graph Convolution

2 code implementations ICLR 2021 Hao Zhu, Piotr Koniusz

Our spectral analysis shows that our simple spectral graph convolution used in S^2GC is a low-pass filter which partitions networks into a few large parts.

Node Classification Node Clustering +1

Imbalance Robust Softmax for Deep Embeeding Learning

no code implementations23 Nov 2020 Hao Zhu, Yang Yuan, Guosheng Hu, Xiang Wu, Neil Robertson

IR-Softmax can generalise to any softmax and its variants (which are discriminative for open-set problem) by directly setting the weights as their class centers, naturally solving the data imbalance problem.

Face Recognition Person Re-Identification

AOT: Appearance Optimal Transport Based Identity Swapping for Forgery Detection

no code implementations NeurIPS 2020 Hao Zhu, Chaoyou Fu, Qianyi Wu, Wayne Wu, Chen Qian, Ran He

However, due to the lack of Deepfakes datasets with large variance in appearance, which can be hardly produced by recent identity swapping methods, the detection algorithm may fail in this situation.

Lets Play Music: Audio-driven Performance Video Generation

no code implementations5 Nov 2020 Hao Zhu, Yi Li, Feixia Zhu, Aihua Zheng, Ran He

We propose a new task named Audio-driven Per-formance Video Generation (APVG), which aims to synthesizethe video of a person playing a certain instrument guided bya given music audio clip.

Frame Video Generation

Multi-agent Trajectory Prediction with Fuzzy Query Attention

1 code implementation NeurIPS 2020 Nitin Kamra, Hao Zhu, Dweep Trivedi, Ming Zhang, Yan Liu

Trajectory prediction for scenes with multiple agents and entities is a challenging problem in numerous domains such as traffic prediction, pedestrian tracking and path planning.

Decision Making Traffic Prediction +1

Using Graph Neural Networks for Mass Spectrometry Prediction

no code implementations9 Oct 2020 Hao Zhu, LiPing Liu, Soha Hassoun

We compare our results to NEIMS, a neural network model that utilizes molecular fingerprints as inputs.

The Return of Lexical Dependencies: Neural Lexicalized PCFGs

3 code implementations29 Jul 2020 Hao Zhu, Yonatan Bisk, Graham Neubig

In this paper we demonstrate that $\textit{context free grammar (CFG) based methods for grammar induction benefit from modeling lexical dependencies}$.

Speech2Video Synthesis with 3D Skeleton Regularization and Expressive Body Poses

1 code implementation17 Jul 2020 Miao Liao, Sibo Zhang, Peng Wang, Hao Zhu, Xinxin Zuo, Ruigang Yang

In this paper, we propose a novel approach to convert given speech audio to a photo-realistic speaking video of a specific person, where the output video has synchronized, realistic, and expressive rich body dynamics.

Additively Homomorphical Encryption based Deep Neural Network for Asymmetrically Collaborative Machine Learning

no code implementations14 Jul 2020 Yifei Zhang, Hao Zhu

For this scheme, we propose a novel privacy-preserving architecture where two parties can collaboratively train a deep learning model efficiently while preserving the privacy of each party's data.

Self-Supervised Human Depth Estimation from Monocular Videos

1 code implementation CVPR 2020 Feitong Tan, Hao Zhu, Zhaopeng Cui, Siyu Zhu, Marc Pollefeys, Ping Tan

Previous methods on estimating detailed human depth often require supervised training with `ground truth' depth data.

Depth Estimation Frame +1

FaceScape: a Large-scale High Quality 3D Face Dataset and Detailed Riggable 3D Face Prediction

1 code implementation CVPR 2020 Haotian Yang, Hao Zhu, Yanru Wang, Mingkai Huang, Qiu Shen, Ruigang Yang, Xun Cao

In this paper, we present a large-scale detailed 3D face dataset, FaceScape, and propose a novel algorithm that is able to predict elaborate riggable 3D face models from a single image input.

SAPIEN: A SimulAted Part-based Interactive ENvironment

1 code implementation CVPR 2020 Fanbo Xiang, Yuzhe Qin, Kaichun Mo, Yikuan Xia, Hao Zhu, Fangchen Liu, Minghua Liu, Hanxiao Jiang, Yifu Yuan, He Wang, Li Yi, Angel X. Chang, Leonidas J. Guibas, Hao Su

To achieve this task, a simulated environment with physically realistic simulation, sufficient articulated objects, and transferability to the real robot is indispensable.

Deep Audio-Visual Learning: A Survey

no code implementations14 Jan 2020 Hao Zhu, Mandi Luo, Rui Wang, Aihua Zheng, Ran He

Audio-visual learning, aimed at exploiting the relationship between audio and visual modalities, has drawn considerable attention since deep learning started to be used successfully.

audio-visual learning Representation Learning

EnsemFDet: An Ensemble Approach to Fraud Detection based on Bipartite Graph

no code implementations23 Dec 2019 Yuxiang Ren, Hao Zhu, Jiawei Zhang, Peng Dai, Liefeng Bo

Existing fraud detection methods try to identify unexpected dense subgraphs and treat related nodes as suspicious.

Fraud Detection

S4G: Amodal Single-view Single-Shot SE(3) Grasp Detection in Cluttered Scenes

no code implementations31 Oct 2019 Yuzhe Qin, Rui Chen, Hao Zhu, Meng Song, Jing Xu, Hao Su

Grasping is among the most fundamental and long-lasting problems in robotics study.

FewRel 2.0: Towards More Challenging Few-Shot Relation Classification

1 code implementation IJCNLP 2019 Tianyu Gao, Xu Han, Hao Zhu, Zhiyuan Liu, Peng Li, Maosong Sun, Jie zhou

We present FewRel 2. 0, a more challenging task to investigate two aspects of few-shot relation classification models: (1) Can they adapt to a new domain with only a handful of instances?

Classification Domain Adaptation +2

Learned Point Cloud Geometry Compression

2 code implementations26 Sep 2019 Jianqiang Wang, Hao Zhu, Zhan Ma, Tong Chen, Haojie Liu, Qiu Shen

This paper presents a novel end-to-end Learned Point Cloud Geometry Compression (a. k. a., Learned-PCGC) framework, to efficiently compress the point cloud geometry (PCG) using deep neural networks (DNN) based variational autoencoders (VAE).

Surface Reconstruction

Quantifying Similarity between Relations with Fact Distribution

1 code implementation ACL 2019 Weize Chen, Hao Zhu, Xu Han, Zhiyuan Liu, Maosong Sun

We introduce a conceptually simple and effective method to quantify the similarity between relations in knowledge bases.

General Classification Open Information Extraction

Ekar: An Explainable Method for Knowledge Aware Recommendation

2 code implementations22 Jun 2019 Weiping Song, Zhijian Duan, Ziqing Yang, Hao Zhu, Ming Zhang, Jian Tang

Recently, a variety of methods have been developed for this problem, which generally try to learn effective representations of users and items and then match items to users according to their representations.

Knowledge-Aware Recommendation Knowledge Graphs +1

Global Convergence of Policy Gradient Methods to (Almost) Locally Optimal Policies

no code implementations19 Jun 2019 Kaiqing Zhang, Alec Koppel, Hao Zhu, Tamer Başar

Under a further strict saddle points assumption, this result establishes convergence to essentially locally-optimal policies of the underlying problem, and thus bridges the gap in existing literature on the convergence of PG methods.

Autonomous Driving Policy Gradient Methods

Neural Finite-State Transducers: Beyond Rational Relations

no code implementations NAACL 2019 Chu-Cheng Lin, Hao Zhu, Matthew R. Gormley, Jason Eisner

We introduce neural finite state transducers (NFSTs), a family of string transduction models defining joint and conditional probability distributions over pairs of strings.

Doc2hash: Learning Discrete Latent variables for Documents Retrieval

1 code implementation NAACL 2019 Yifei Zhang, Hao Zhu

However, the discrete stochastic layer is usually incompatible with the backpropagation in the training stage, and thus causes a gradient flow problem because of non-differentiable operators.

Detailed Human Shape Estimation from a Single Image by Hierarchical Mesh Deformation

1 code implementation CVPR 2019 Hao Zhu, Xinxin Zuo, Sen Wang, Xun Cao, Ruigang Yang

This paper presents a novel framework to recover detailed human body shapes from a single image.

Breaking the Spatio-Angular Trade-off for Light Field Super-Resolution via LSTM Modelling on Epipolar Plane Images

no code implementations15 Feb 2019 Hao Zhu, Mantang Guo, Hongdong Li, Qing Wang, Antonio Robles-Kelly

We prove that the light field is a 2D series, thus, a specifically designed CNN-LSTM network is proposed to capture the continuity property of the EPI.

Super-Resolution

Arbitrary Talking Face Generation via Attentional Audio-Visual Coherence Learning

no code implementations17 Dec 2018 Hao Zhu, Huaibo Huang, Yi Li, Aihua Zheng, Ran He

Talking face generation aims to synthesize a face video with precise lip synchronization as well as a smooth transition of facial motion over the entire video via the given speech clip and facial image.

Talking Face Generation

CrowdPose: Efficient Crowded Scenes Pose Estimation and A New Benchmark

3 code implementations CVPR 2019 Jiefeng Li, Can Wang, Hao Zhu, Yihuan Mao, Hao-Shu Fang, Cewu Lu

In this paper, we propose a novel and efficient method to tackle the problem of pose estimation in the crowd and a new dataset to better evaluate algorithms.

Keypoint Detection Multi-Person Pose Estimation

Language Modeling with Sparse Product of Sememe Experts

1 code implementation EMNLP 2018 Yihong Gu, Jun Yan, Hao Zhu, Zhiyuan Liu, Ruobing Xie, Maosong Sun, Fen Lin, Leyu Lin

Most language modeling methods rely on large-scale data to statistically learn the sequential patterns of words.

Language Modelling

Cross-lingual Lexical Sememe Prediction

1 code implementation EMNLP 2018 Fanchao Qi, Yankai Lin, Maosong Sun, Hao Zhu, Ruobing Xie, Zhiyuan Liu

We propose a novel framework to model correlations between sememes and multi-lingual words in low-dimensional semantic space for sememe prediction.

cross-lingual sememe prediction Learning Word Embeddings +1

Incorporating Chinese Characters of Words for Lexical Sememe Prediction

1 code implementation ACL 2018 Huiming Jin, Hao Zhu, Zhiyuan Liu, Ruobing Xie, Maosong Sun, Fen Lin, Leyu Lin

However, existing methods of lexical sememe prediction typically rely on the external context of words to represent the meaning, which usually fails to deal with low-frequency and out-of-vocabulary words.

Common Sense Reasoning

Barotropic instability of shear flows

no code implementations3 Jan 2018 Zhiwu Lin, Jincheng Yang, Hao Zhu

The second one is to write the linearized fluid equation in a Hamiltonian form and then use an instability index theory for general Hamiltonian PDEs.

Analysis of PDEs

Light Field Segmentation From Super-pixel Graph Representation

no code implementations20 Dec 2017 Xianqiang Lv, Hao Zhu, Qing Wang

The large volume of input data and the redundancy of light field make it an open challenge.

4D Light Field Superpixel and Segmentation

no code implementations CVPR 2017 Hao Zhu, Qi Zhang, Qing Wang

Superpixel segmentation of 2D image has been widely used in many computer vision tasks.

Decentralized learning for wireless communications and networking

no code implementations30 Mar 2015 Georgios B. Giannakis, Qing Ling, Gonzalo Mateos, Ioannis D. Schizas, Hao Zhu

This chapter deals with decentralized learning algorithms for in-network processing of graph-valued data.

Spectrum Cartography

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