Search Results for author: Zhen Xu

Found 43 papers, 15 papers with code

Unveiling the Lexical Sensitivity of LLMs: Combinatorial Optimization for Prompt Enhancement

no code implementations31 May 2024 Pengwei Zhan, Zhen Xu, Qian Tan, Jie Song, Ru Xie

Large language models (LLMs) demonstrate exceptional instruct-following ability to complete various downstream tasks.

Combinatorial Optimization

EasyVolcap: Accelerating Neural Volumetric Video Research

1 code implementation11 Dec 2023 Zhen Xu, Tao Xie, Sida Peng, Haotong Lin, Qing Shuai, Zhiyuan Yu, Guangzhao He, Jiaming Sun, Hujun Bao, Xiaowei Zhou

Volumetric video is a technology that digitally records dynamic events such as artistic performances, sporting events, and remote conversations.

4K4D: Real-Time 4D View Synthesis at 4K Resolution

no code implementations CVPR 2024 Zhen Xu, Sida Peng, Haotong Lin, Guangzhao He, Jiaming Sun, Yujun Shen, Hujun Bao, Xiaowei Zhou

Experiments show that our representation can be rendered at over 400 FPS on the DNA-Rendering dataset at 1080p resolution and 80 FPS on the ENeRF-Outdoor dataset at 4K resolution using an RTX 4090 GPU, which is 30x faster than previous methods and achieves the state-of-the-art rendering quality.

4k

Relightable and Animatable Neural Avatar from Sparse-View Video

no code implementations CVPR 2024 Zhen Xu, Sida Peng, Chen Geng, Linzhan Mou, Zihan Yan, Jiaming Sun, Hujun Bao, Xiaowei Zhou

Based on the HDQ algorithm, we leverage sphere tracing to efficiently estimate the surface intersection and light visibility.

Inverse Rendering

Learning Neural Volumetric Representations of Dynamic Humans in Minutes

1 code implementation CVPR 2023 Chen Geng, Sida Peng, Zhen Xu, Hujun Bao, Xiaowei Zhou

In this paper, we propose a novel method for learning neural volumetric videos of dynamic humans from sparse view videos in minutes with competitive visual quality.

Text-Guided Unsupervised Latent Transformation for Multi-Attribute Image Manipulation

no code implementations CVPR 2023 Xiwen Wei, Zhen Xu, Cheng Liu, Si Wu, Zhiwen Yu, Hau San Wong

To address this limitation, we propose a Text-guided Unsupervised StyleGAN Latent Transformation (TUSLT) model, which adaptively infers a single transformation step in the latent space of StyleGAN to simultaneously manipulate multiple attributes on a given input image.

Attribute Image Manipulation +2

Blemish-Aware and Progressive Face Retouching With Limited Paired Data

no code implementations CVPR 2023 Lianxin Xie, Wen Xue, Zhen Xu, Si Wu, Zhiwen Yu, Hau San Wong

It is worth noting that we reduce the dependence of BPFRe on paired training samples by imposing effective regularization on unpaired ones.

Decoder Image-to-Image Translation

Bridging the Gap of AutoGraph between Academia and Industry: Analysing AutoGraph Challenge at KDD Cup 2020

1 code implementation6 Apr 2022 Zhen Xu, Lanning Wei, Huan Zhao, Rex Ying, Quanming Yao, Wei-Wei Tu, Isabelle Guyon

Researchers naturally adopt Automated Machine Learning on Graph Learning, aiming to reduce the human effort and achieve generally top-performing GNNs, but their methods focus more on the architecture search.

Graph Learning Neural Architecture Search +1

Animatable Implicit Neural Representations for Creating Realistic Avatars from Videos

1 code implementation15 Mar 2022 Sida Peng, Zhen Xu, Junting Dong, Qianqian Wang, Shangzhan Zhang, Qing Shuai, Hujun Bao, Xiaowei Zhou

Some recent works have proposed to decompose a non-rigidly deforming scene into a canonical neural radiance field and a set of deformation fields that map observation-space points to the canonical space, thereby enabling them to learn the dynamic scene from images.

360-Attack: Distortion-Aware Perturbations From Perspective-Views

no code implementations CVPR 2022 Yunjian Zhang, Yanwei Liu, Jinxia Liu, Jingbo Miao, Antonios Argyriou, Liming Wang, Zhen Xu

In this paper, we propose an adversarial attack targeting spherical images, called 360-attactk, that transfers adversarial perturbations from perspective-view (PV) images to a final adversarial spherical image.

Adversarial Attack

Efficient Neural Radiance Fields for Interactive Free-viewpoint Video

no code implementations2 Dec 2021 Haotong Lin, Sida Peng, Zhen Xu, Yunzhi Yan, Qing Shuai, Hujun Bao, Xiaowei Zhou

We propose a novel scene representation, called ENeRF, for the fast creation of interactive free-viewpoint videos.

Depth Estimation Depth Prediction +1

Confidence Propagation Cluster: Unleash Full Potential of Object Detectors

1 code implementation CVPR 2022 Yichun Shen, Wanli Jiang, Zhen Xu, Rundong Li, Junghyun Kwon, Siyi Li

It has been a long history that most object detection methods obtain objects by using the non-maximum suppression (NMS) and its improved versions like Soft-NMS to remove redundant bounding boxes.

Object object-detection +1

Codabench: Flexible, Easy-to-Use and Reproducible Benchmarking Platform

2 code implementations12 Oct 2021 Zhen Xu, Sergio Escalera, Isabelle Guyon, Adrien Pavão, Magali Richard, Wei-Wei Tu, Quanming Yao, Huan Zhao

A public instance of Codabench (https://www. codabench. org/) is open to everyone, free of charge, and allows benchmark organizers to compare fairly submissions, under the same setting (software, hardware, data, algorithms), with custom protocols and data formats.

Benchmarking

AutoML Meets Time Series Regression Design and Analysis of the AutoSeries Challenge

1 code implementation28 Jul 2021 Zhen Xu, Wei-Wei Tu, Isabelle Guyon

Driven by business scenarios, we organized the first Automated Time Series Regression challenge (AutoSeries) for the WSDM Cup 2020.

AutoML Feature Engineering +3

BEDS-Bench: Behavior of EHR-models under Distributional Shift--A Benchmark

1 code implementation17 Jul 2021 Anand Avati, Martin Seneviratne, Emily Xue, Zhen Xu, Balaji Lakshminarayanan, Andrew M. Dai

Most ML approaches focus on generalization performance on unseen data that are similar to the training data (In-Distribution, or IND).

MatchVIE: Exploiting Match Relevancy between Entities for Visual Information Extraction

no code implementations24 Jun 2021 Guozhi Tang, Lele Xie, Lianwen Jin, Jiapeng Wang, Jingdong Chen, Zhen Xu, Qianying Wang, Yaqiang Wu, Hui Li

Through key-value matching based on relevancy evaluation, the proposed MatchVIE can bypass the recognitions to various semantics, and simply focuses on the strong relevancy between entities.

Graph Neural Network

MUFASA: Multimodal Fusion Architecture Search for Electronic Health Records

no code implementations3 Feb 2021 Zhen Xu, David R. So, Andrew M. Dai

One important challenge of applying deep learning to electronic health records (EHR) is the complexity of their multimodal structure.

Neural Architecture Search

NeoRL: A Near Real-World Benchmark for Offline Reinforcement Learning

3 code implementations1 Feb 2021 Rongjun Qin, Songyi Gao, Xingyuan Zhang, Zhen Xu, Shengkai Huang, Zewen Li, Weinan Zhang, Yang Yu

We evaluate existing offline RL algorithms on NeoRL and argue that the performance of a policy should also be compared with the deterministic version of the behavior policy, instead of the dataset reward.

Offline RL reinforcement-learning +1

Solution landscapes of the diblock copolymer-homopolymer model under two-dimensional confinement

no code implementations26 Jan 2021 Zhen Xu, Yucen Han, Jianyuan Yin, Bing Yu, Yasumasa Nishiura, Lei Zhang

We investigate the solution landscapes of the confined diblock copolymer and homopolymer in two-dimensional domain by using the extended Ohta--Kawasaki model.

Soft Condensed Matter Computational Physics

AutoSpeech 2020: The Second Automated Machine Learning Challenge for Speech Classification

no code implementations25 Oct 2020 Jingsong Wang, Tom Ko, Zhen Xu, Xiawei Guo, Souxiang Liu, Wei-Wei Tu, Lei Xie

The AutoSpeech challenge calls for automated machine learning (AutoML) solutions to automate the process of applying machine learning to speech processing tasks.

AutoML BIG-bench Machine Learning +1

Deep Physiological State Space Model for Clinical Forecasting

no code implementations4 Dec 2019 Yuan Xue, Denny Zhou, Nan Du, Andrew Dai, Zhen Xu, Kun Zhang, Claire Cui

Clinical forecasting based on electronic medical records (EMR) can uncover the temporal correlations between patients' conditions and outcomes from sequences of longitudinal clinical measurements.

Beyond Adaptive Submodularity: Adaptive Influence Maximization with Intermediary Constraints

no code implementations8 Nov 2019 Shatian Wang, Zhen Xu, Van-Anh Truong

We consider a brand with a given budget that wants to promote a product over multiple rounds of influencer marketing.

Decision Making Marketing

LocalGAN: Modeling Local Distributions for Adversarial Response Generation

no code implementations25 Sep 2019 Zhen Xu, Baoxun Wang, huan zhang, Kexin Qiu, Deyuan Zhang, Chengjie Sun

This paper presents a new methodology for modeling the local semantic distribution of responses to a given query in the human-conversation corpus, and on this basis, explores a specified adversarial learning mechanism for training Neural Response Generation (NRG) models to build conversational agents.

Response Generation

Learning an Adaptive Learning Rate Schedule

no code implementations20 Sep 2019 Zhen Xu, Andrew M. Dai, Jonas Kemp, Luke Metz

The learning rate is one of the most important hyper-parameters for model training and generalization.

Learning the Graphical Structure of Electronic Health Records with Graph Convolutional Transformer

2 code implementations11 Jun 2019 Edward Choi, Zhen Xu, Yujia Li, Michael W. Dusenberry, Gerardo Flores, Yuan Xue, Andrew M. Dai

A recent study showed that using the graphical structure underlying EHR data (e. g. relationship between diagnoses and treatments) improves the performance of prediction tasks such as heart failure prediction.

Graph Reconstruction Readmission Prediction +1

LSDSCC: a Large Scale Domain-Specific Conversational Corpus for Response Generation with Diversity Oriented Evaluation Metrics

no code implementations NAACL 2018 Zhen Xu, Nan Jiang, Bingquan Liu, Wenge Rong, Bowen Wu, Baoxun Wang, Zhuoran Wang, Xiaolong Wang

The experimental results have shown that our proposed corpus can be taken as a new benchmark dataset for the NRG task, and the presented metrics are promising to guide the optimization of NRG models by quantifying the diversity of the generated responses reasonably.

Machine Translation Response Generation

Group Linguistic Bias Aware Neural Response Generation

no code implementations WS 2017 Jianan Wang, Xin Wang, Fang Li, Zhen Xu, Zhuoran Wang, Baoxun Wang

For practical chatbots, one of the essential factor for improving user experience is the capability of customizing the talking style of the agents, that is, to make chatbots provide responses meeting users{'} preference on language styles, topics, etc.

Decoder Response Generation

Neural Response Generation via GAN with an Approximate Embedding Layer

no code implementations EMNLP 2017 Zhen Xu, Bingquan Liu, Baoxun Wang, Chengjie Sun, Xiaolong Wang, Zhuoran Wang, Chao Qi

This paper presents a Generative Adversarial Network (GAN) to model single-turn short-text conversations, which trains a sequence-to-sequence (Seq2Seq) network for response generation simultaneously with a discriminative classifier that measures the differences between human-produced responses and machine-generated ones.

Generative Adversarial Network Machine Translation +1

Using Social Dynamics to Make Individual Predictions: Variational Inference with a Stochastic Kinetic Model

no code implementations NeurIPS 2016 Zhen Xu, Wen Dong, Sargur Srihari

Social dynamics is concerned primarily with interactions among individuals and the resulting group behaviors, modeling the temporal evolution of social systems via the interactions of individuals within these systems.

Variational Inference

Incorporating Loose-Structured Knowledge into Conversation Modeling via Recall-Gate LSTM

1 code implementation17 May 2016 Zhen Xu, Bingquan Liu, Baoxun Wang, Chengjie Sun, Xiaolong Wang

Modeling human conversations is the essence for building satisfying chat-bots with multi-turn dialog ability.

Activity Auto-Completion: Predicting Human Activities From Partial Videos

no code implementations ICCV 2015 Zhen Xu, Laiyun Qing, Jun Miao

Finally, the missing observation of an activity is predicted as the activity candidates provided by the auto-completion model.

Activity Prediction Information Retrieval +2

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