Search Results for author: YuAn Liu

Found 26 papers, 8 papers with code

Object Tracking using Spatio-Temporal Networks for Future Prediction Location

no code implementations ECCV 2020 Yuan Liu, Ruoteng Li, Yu Cheng, Robby T. Tan, Xiubao Sui

To facilitate the future prediction ability, we follow three key observations: 1) object motion trajectory is affected significantly by camera motion; 2) the past trajectory of an object can act as a salient cue to estimate the object motion in the spatial domain; 3) previous frames contain the surroundings and appearance of the target object, which is useful for predicting the target object’s future locations.

Future prediction Object Tracking

Harmonic Modeling, Data Generation, and Analysis of Power Electronics-Interfaced Residential Loads

no code implementations5 Nov 2021 Ankit Singhal, Dexin Wang, Andrew P. Reiman, YuAn Liu, Donald J. Hammerstrom, Soumya Kundu

Integration of electronics-based residential appliances and distributed energy resources in homes is expected to rise with grid decarbonization.

You Only Hypothesize Once: Point Cloud Registration with Rotation-equivariant Descriptors

1 code implementation1 Sep 2021 Haiping Wang, YuAn Liu, Zhen Dong, Wenping Wang, Bisheng Yang

In this paper, we propose a novel local descriptor-based framework, called You Only Hypothesize Once (YOHO), for the registration of two unaligned point clouds.

Point Cloud Registration

Improving 3D Object Detection with Channel-wise Transformer

1 code implementation ICCV 2021 Hualian Sheng, Sijia Cai, YuAn Liu, Bing Deng, Jianqiang Huang, Xian-Sheng Hua, Min-Jian Zhao

Though 3D object detection from point clouds has achieved rapid progress in recent years, the lack of flexible and high-performance proposal refinement remains a great hurdle for existing state-of-the-art two-stage detectors.

3D Object Detection Region Proposal

AdaFit: Rethinking Learning-based Normal Estimation on Point Clouds

1 code implementation ICCV 2021 Runsong Zhu, YuAn Liu, Zhen Dong, Tengping Jiang, YuAn Wang, Wenping Wang, Bisheng Yang

Existing works use a network to learn point-wise weights for weighted least squares surface fitting to estimate the normals, which has difficulty in finding accurate normals in complex regions or containing noisy points.

A Contract Theory based Incentive Mechanism for Federated Learning

no code implementations12 Aug 2021 Mengmeng Tian, Yuxin Chen, YuAn Liu, Zehui Xiong, Cyril Leung, Chunyan Miao

It is challenging to design proper incentives for the FL clients due to the fact that the task is privately trained by the clients.

Federated Learning

Neural Rays for Occlusion-aware Image-based Rendering

no code implementations28 Jul 2021 YuAn Liu, Sida Peng, Lingjie Liu, Qianqian Wang, Peng Wang, Christian Theobalt, Xiaowei Zhou, Wenping Wang

Experiments demonstrate that NeuRay can quickly generate high-quality novel view images of unseen scenes with little finetuning and can handle complex scenes with severe self-occlusions which previous methods struggle with.

Neural Rendering Novel View Synthesis +1

NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction

2 code implementations NeurIPS 2021 Peng Wang, Lingjie Liu, YuAn Liu, Christian Theobalt, Taku Komura, Wenping Wang

In NeuS, we propose to represent a surface as the zero-level set of a signed distance function (SDF) and develop a new volume rendering method to train a neural SDF representation.

Novel View Synthesis Surface Reconstruction

Noise Is Useful: Exploiting Data Diversity for Edge Intelligence

no code implementations14 Jan 2021 Zhi Zeng, YuAn Liu, Weijun Tang, Fangjiong Chen

Edge intelligence requires to fast access distributed data samples generated by edge devices.

Information Theory Information Theory

Contrast and Order Representations for Video Self-Supervised Learning

no code implementations ICCV 2021 Kai Hu, Jie Shao, YuAn Liu, Bhiksha Raj, Marios Savvides, Zhiqiang Shen

To address this, we present a contrast-and-order representation (CORP) framework for learning self-supervised video representations that can automatically capture both the appearance information within each frame and temporal information across different frames.

Action Recognition Self-Supervised Learning

Learnable Motion Coherence for Correspondence Pruning

no code implementations CVPR 2021 YuAn Liu, Lingjie Liu, Cheng Lin, Zhen Dong, Wenping Wang

We propose a novel formulation of fitting coherent motions with a smooth function on a graph of correspondences and show that this formulation allows a closed-form solution by graph Laplacian.

Pose Estimation

Object Tracking Using Spatio-Temporal Future Prediction

no code implementations15 Oct 2020 YuAn Liu, Ruoteng Li, Robby T. Tan, Yu Cheng, Xiubao Sui

Our trajectory prediction module predicts the target object's locations in the current and future frames based on the object's past trajectory.

Future prediction Object Tracking +1

Addressing the Real-world Class Imbalance Problem in Dermatology

no code implementations9 Oct 2020 Wei-Hung Weng, Jonathan Deaton, Vivek Natarajan, Gamaleldin F. Elsayed, YuAn Liu

Class imbalance is a common problem in medical diagnosis, causing a standard classifier to be biased towards the common classes and perform poorly on the rare classes.

Few-Shot Learning Medical Diagnosis

Accelerated Deep Reinforcement Learning Based Load Shedding for Emergency Voltage Control

no code implementations22 Jun 2020 Renke Huang, Yujiao Chen, Tianzhixi Yin, Xinya Li, Ang Li, Jie Tan, Wenhao Yu, YuAn Liu, Qiuhua Huang

Load shedding has been one of the most widely used and effective emergency control approaches against voltage instability.

FedCoin: A Peer-to-Peer Payment System for Federated Learning

1 code implementation26 Feb 2020 Yuan Liu, Shuai Sun, Zhengpeng Ai, Shuangfeng Zhang, Zelei Liu, Han Yu

In FedCoin, blockchain consensus entities calculate SVs and a new block is created based on the proof of Shapley (PoSap) protocol.

Federated Learning

GIFT: Learning Transformation-Invariant Dense Visual Descriptors via Group CNNs

1 code implementation NeurIPS 2019 Yuan Liu, Zehong Shen, Zhixuan Lin, Sida Peng, Hujun Bao, Xiaowei Zhou

Instead of feature pooling, we use group convolutions to exploit underlying structures of the extracted features on the group, resulting in descriptors that are both discriminative and provably invariant to the group of transformations.

Pose Estimation

A deep learning system for differential diagnosis of skin diseases

no code implementations11 Sep 2019 Yuan Liu, Ayush Jain, Clara Eng, David H. Way, Kang Lee, Peggy Bui, Kimberly Kanada, Guilherme de Oliveira Marinho, Jessica Gallegos, Sara Gabriele, Vishakha Gupta, Nalini Singh, Vivek Natarajan, Rainer Hofmann-Wellenhof, Greg S. Corrado, Lily H. Peng, Dale R. Webster, Dennis Ai, Susan Huang, Yun Liu, R. Carter Dunn, David Coz

In this paper, we developed a deep learning system (DLS) to provide a differential diagnosis of skin conditions for clinical cases (skin photographs and associated medical histories).

Multi-granularity Generator for Temporal Action Proposal

no code implementations CVPR 2019 Yuan Liu, Lin Ma, Yifeng Zhang, Wei Liu, Shih-Fu Chang

In this paper, we propose a multi-granularity generator (MGG) to perform the temporal action proposal from different granularity perspectives, relying on the video visual features equipped with the position embedding information.

Action Recognition Temporal Action Proposal Generation

An Attention-Based Approach for Single Image Super Resolution

no code implementations18 Jul 2018 Yuan Liu, Yuancheng Wang, Nan Li, Xu Cheng, Yifeng Zhang, Yongming Huang, Guojun Lu

We propose an attention-based approach to give a discrimination between texture areas and smooth areas.

Image Super-Resolution

Best Vision Technologies Submission to ActivityNet Challenge 2018-Task: Dense-Captioning Events in Videos

no code implementations25 Jun 2018 Yuan Liu, Moyini Yao

This note describes the details of our solution to the dense-captioning events in videos task of ActivityNet Challenge 2018.

Optical Flow Estimation Video Captioning

Une véritable approche $\ell_0$ pour l'apprentissage de dictionnaire

no code implementations12 Sep 2017 Yuan Liu, Stéphane Canu, Paul Honeine, Su Ruan

Sparse representation learning has recently gained a great success in signal and image processing, thanks to recent advances in dictionary learning.

Dictionary Learning Image Denoising +1

Cannot find the paper you are looking for? You can Submit a new open access paper.