Search Results for author: Yifan Wang

Found 30 papers, 4 papers with code

CLIFFNet for Monocular Depth Estimation with Hierarchical Embedding Loss

no code implementations ECCV 2020 Lijun Wang, Jianming Zhang, Yifan Wang, Huchuan Lu, Xiang Ruan

This paper proposes a hierarchical loss for monocular depth estimation, which measures the differences between the prediction and ground truth in hierarchical embedding spaces of depth maps.

Monocular Depth Estimation

RoR: Read-over-Read for Long Document Machine Reading Comprehension

no code implementations10 Sep 2021 Jing Zhao, Junwei Bao, Yifan Wang, Yongwei Zhou, Youzheng Wu, Xiaodong He, BoWen Zhou

To address this problem, we propose RoR, a read-over-read method, which expands the reading field from chunk to document.

Machine Reading Comprehension

CUSTOM: Aspect-Oriented Product Summarization for E-Commerce

no code implementations18 Aug 2021 Jiahui Liang, Junwei Bao, Yifan Wang, Youzheng Wu, Xiaodong He, BoWen Zhou

To address the problem, we propose CUSTOM, aspect-oriented product summarization for e-commerce, which generates diverse and controllable summaries towards different product aspects.

DisenHAN: Disentangled Heterogeneous Graph Attention Network for Recommendation

no code implementations21 Jun 2021 Yifan Wang, Suyao Tang, Yuntong Lei, Weiping Song, Sheng Wang, Ming Zhang

In this paper, we propose a novel disentangled heterogeneous graph attention network DisenHAN for top-$N$ recommendation, which learns disentangled user/item representations from different aspects in a heterogeneous information network.

Graph Attention Recommendation Systems

SGG: Learning to Select, Guide, and Generate for Keyphrase Generation

no code implementations NAACL 2021 Jing Zhao, Junwei Bao, Yifan Wang, Youzheng Wu, Xiaodong He, BoWen Zhou

Keyphrases, that concisely summarize the high-level topics discussed in a document, can be categorized into present keyphrase which explicitly appears in the source text, and absent keyphrase which does not match any contiguous subsequence but is highly semantically related to the source.

Text Generation

Repopulating Street Scenes

no code implementations CVPR 2021 Yifan Wang, Andrew Liu, Richard Tucker, Jiajun Wu, Brian L. Curless, Steven M. Seitz, Noah Snavely

We present a framework for automatically reconfiguring images of street scenes by populating, depopulating, or repopulating them with objects such as pedestrians or vehicles.

Autonomous Driving

DynOcc: Learning Single-View Depth from Dynamic Occlusion Cues

no code implementations30 Mar 2021 Yifan Wang, Linjie Luo, Xiaohui Shen, Xing Mei

Recently, significant progress has been made in single-view depth estimation thanks to increasingly large and diverse depth datasets.

3D Reconstruction Autonomous Driving +2

Defect $a$-Theorem and $a$-Maximization

no code implementations29 Jan 2021 Yifan Wang

We derive the anomaly multiplet relations that express the defect $a$- and $c$-anomalies in terms of the defect (mixed) 't Hooft anomalies for this $U(1)_R$ symmetry.

High Energy Physics - Theory

Anomalous Symmetries End at the Boundary

no code implementations31 Dec 2020 Ryan Thorngren, Yifan Wang

We then recast the problem in terms of symmetry defects and find the same conclusions for anomalies of discrete and orientation-reversing global symmetries, up to the conjecture that global gravitational anomalies, which may not be associated with any diffeomorphism symmetry, also forbid the existence of boundary conditions.

High Energy Physics - Theory Strongly Correlated Electrons

Surface Defect, Anomalies and $b$-Extremization

no code implementations11 Dec 2020 Yifan Wang

The $b$-theorem states that $b$ must monotonically decrease under defect RG flows and was proven by coupling to a spurious defect dilaton.

High Energy Physics - Theory

Low-Resolution Face Recognition In Resource-Constrained Environments

no code implementations23 Nov 2020 Mozhdeh Rouhsedaghat, Yifan Wang, Shuowen Hu, Suya You, C. -C. Jay Kuo

A non-parametric low-resolution face recognition model for resource-constrained environments with limited networking and computing is proposed in this work.

Active Learning Face Recognition

VC-Net: Deep Volume-Composition Networks for Segmentation and Visualization of Highly Sparse and Noisy Image Data

no code implementations14 Sep 2020 Yifan Wang, Guoli Yan, Haikuan Zhu, Sagar Buch, Ying Wang, Ewart Mark Haacke, Jing Hua, Zichun Zhong

A multi-stream convolutional neural network is proposed to learn the 3D volume and 2D MIP features respectively and then explore their inter-dependencies in a joint volume-composition embedding space by unprojecting the MIP features into 3D volume embedding space.

FaceHop: A Light-Weight Low-Resolution Face Gender Classification Method

no code implementations18 Jul 2020 Mozhdeh Rouhsedaghat, Yifan Wang, Xiou Ge, Shuowen Hu, Suya You, C. -C. Jay Kuo

For gray-scale face images of resolution $32 \times 32$ in the LFW and the CMU Multi-PIE datasets, FaceHop achieves correct gender classification rates of 94. 63% and 95. 12% with model sizes of 16. 9K and 17. 6K parameters, respectively.

Classification General Classification

People as Scene Probes

no code implementations ECCV 2020 Yifan Wang, Brian Curless, Steve Seitz

By analyzing the motion of people and other objects in a scene, we demonstrate how to infer depth, occlusion, lighting, and shadow information from video taken from a single camera viewpoint.

Depth Estimation

Attention: to Better Stand on the Shoulders of Giants

no code implementations27 May 2020 Sha Yuan, Zhou Shao, Yu Zhang, Xingxing Wei, Tong Xiao, Yifan Wang, Jie Tang

In the progress of science, the previously discovered knowledge principally inspires new scientific ideas, and citation is a reasonably good reflection of this cumulative nature of scientific research.

PointHop++: A Lightweight Learning Model on Point Sets for 3D Classification

2 code implementations9 Feb 2020 Min Zhang, Yifan Wang, Pranav Kadam, Shan Liu, C. -C. Jay Kuo

The PointHop method was recently proposed by Zhang et al. for 3D point cloud classification with unsupervised feature extraction.

3D Classification 3D Point Cloud Classification +3

OpenEI: An Open Framework for Edge Intelligence

no code implementations5 Jun 2019 Xingzhou Zhang, Yifan Wang, Sidi Lu, Liangkai Liu, Lanyu Xu, Weisong Shi

At the same time, we have witnessed the proliferation of AI algorithms and models which accelerate the successful deployment of intelligence mainly in cloud services.

Edge-computing

pCAMP: Performance Comparison of Machine Learning Packages on the Edges

no code implementations5 Jun 2019 Xingzhou Zhang, Yifan Wang, Weisong Shi

However, little research has been done to evaluate these packages on the edges, making it difficult for end users to select an appropriate pair of software and hardware.

Session-based Social Recommendation via Dynamic Graph Attention Networks

2 code implementations25 Feb 2019 Weiping Song, Zhiping Xiao, Yifan Wang, Laurent Charlin, Ming Zhang, Jian Tang

However, recommendation in online communities is a challenging problem: 1) users' interests are dynamic, and 2) users are influenced by their friends.

 Ranked #1 on Recommendation Systems on Douban (NDCG metric)

Graph Attention Recommendation Systems

Dual Principal Component Pursuit: Probability Analysis and Efficient Algorithms

no code implementations24 Dec 2018 Zhihui Zhu, Yifan Wang, Daniel P. Robinson, Daniel Q. Naiman, Rene Vidal, Manolis C. Tsakiris

However, its geometric analysis is based on quantities that are difficult to interpret and are not amenable to statistical analysis.

Dual Principal Component Pursuit: Improved Analysis and Efficient Algorithms

no code implementations NeurIPS 2018 Zhihui Zhu, Yifan Wang, Daniel Robinson, Daniel Naiman, Rene Vidal, Manolis Tsakiris

However, its geometric analysis is based on quantities that are difficult to interpret and are not amenable to statistical analysis.

Modeling and Predicting Citation Count via Recurrent Neural Network with Long Short-Term Memory

no code implementations6 Nov 2018 Sha Yuan, Jie Tang, Yu Zhang, Yifan Wang, Tong Xiao

The rapid evolution of scientific research has been creating a huge volume of publications every year.

Digital Libraries Physics and Society

CAVBench: A Benchmark Suite for Connected and Autonomous Vehicles

no code implementations15 Oct 2018 Yifan Wang, Shaoshan Liu, Xiaopei Wu, Weisong Shi

Meanwhile, several pioneer efforts have focused on the edge computing system and architecture design for the CAVs scenario and provided various heterogeneous platform prototypes for CAVs.

Distributed, Parallel, and Cluster Computing Performance

Identifying Outlier Arms in Multi-Armed Bandit

no code implementations NeurIPS 2017 Honglei Zhuang, Chi Wang, Yifan Wang

Outlier detection is a powerful method to narrow down the attention to a few objects after the data for them are collected.

Outlier Detection

MarrNet: 3D Shape Reconstruction via 2.5D Sketches

no code implementations NeurIPS 2017 Jiajun Wu, Yifan Wang, Tianfan Xue, Xingyuan Sun, William T. Freeman, Joshua B. Tenenbaum

First, compared to full 3D shape, 2. 5D sketches are much easier to be recovered from a 2D image; models that recover 2. 5D sketches are also more likely to transfer from synthetic to real data.

3D Object Reconstruction From A Single Image 3D Reconstruction +2

(2,2) Superconformal Bootstrap in Two Dimensions

no code implementations17 Oct 2016 Ying-Hsuan Lin, Shu-Heng Shao, Yifan Wang, Xi Yin

We find a simple relation between two-dimensional BPS N=2 superconformal blocks and bosonic Virasoro conformal blocks, which allows us to analyze the crossing equations for BPS 4-point functions in unitary (2, 2) superconformal theories numerically with semidefinite programming.

High Energy Physics - Theory

End-to-End Image Super-Resolution via Deep and Shallow Convolutional Networks

no code implementations26 Jul 2016 Yifan Wang, Lijun Wang, Hongyu Wang, Peihua Li

In this paper, we seek an alternative and propose a new image SR method, which jointly learns the feature extraction, upsampling and HR reconstruction modules, yielding a completely end-to-end trainable deep CNN.

Image Super-Resolution

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