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.
1 code implementation • 4 Mar 2023 • YuAn Liu, Songyang Zhang, Jiacheng Chen, Kai Chen, Dahua Lin
Masked Image Modeling (MIM) has achieved promising progress with the advent of Masked Autoencoders (MAE) and BEiT.
no code implementations • 29 Jan 2023 • YuAn Liu, Mu Niu, Claire Miller
Motivated by the success of Bayesian optimisation algorithms in the Euclidean space, we propose a novel approach to construct Intrinsic Bayesian optimisation (In-BO) on manifolds with a primary focus on complex constrained domains or irregular-shaped spaces arising as submanifolds of R2, R3 and beyond.
no code implementations • 21 Dec 2022 • YuAn Liu, Jiacheng Chen, Hao Wu
Learning effective motion features is an essential pursuit of video representation learning.
1 code implementation • 17 Dec 2022 • Tao Sheng, Chengchao Shen, YuAn Liu, Yeyu Ou, Zhe Qu, Jianxin Wang
It introduces a global Generative Adversarial Network to model the global data distribution without access to local datasets, so the global model can be trained using the global information of data distribution without privacy leakage.
no code implementations • 17 Dec 2022 • Sayak Mukherjee, Ramij R. Hossain, YuAn Liu, Wei Du, Veronica Adetola, Sheik M. Mohiuddin, Qiuhua Huang, Tianzhixi Yin, Ankit Singhal
This paper presents a novel federated reinforcement learning (Fed-RL) methodology to enhance the cyber resiliency of networked microgrids.
no code implementations • 11 Dec 2022 • Jiarong Yang, YuAn Liu, Rahif Kassab
Distributed Stein Variational Gradient Descent (DSVGD) is a non-parametric distributed learning framework for federated Bayesian learning, where multiple clients jointly train a machine learning model by communicating a number of non-random and interacting particles with the server.
no code implementations • 11 Dec 2022 • Peng Jia, Wenbo Liu, YuAn Liu, Haiwu Pan
Then an algorithm based on morphological operations and two neural networks would be used to detect candidates of celestial objects with different flux from these 2D images.
no code implementations • 6 Dec 2022 • Ramij R. Hossain, Tianzhixi Yin, Yan Du, Renke Huang, Jie Tan, Wenhao Yu, YuAn Liu, Qiuhua Huang
We propose a novel model-based-DRL framework where a deep neural network (DNN)-based dynamic surrogate model, instead of a real-world power-grid or physics-based simulation, is utilized with the policy learning framework, making the process faster and sample efficient.
no code implementations • 30 Nov 2022 • Yu Fang, Lanzhuju Mei, Changjian Li, YuAn Liu, Wenping Wang, Zhiming Cui, Dinggang Shen
Cone beam computed tomography (CBCT) has been widely used in clinical practice, especially in dental clinics, while the radiation dose of X-rays when capturing has been a long concern in CBCT imaging.
no code implementations • 25 Nov 2022 • Xiaoxiao Long, Cheng Lin, Lingjie Liu, YuAn Liu, Peng Wang, Christian Theobalt, Taku Komura, Wenping Wang
In this paper, we propose to represent surfaces as the Unsigned Distance Function (UDF) and develop a new volume rendering scheme to learn the neural UDF representation.
no code implementations • 23 Nov 2022 • Haoxin Li, Yue Wu, YuAn Liu, Hanwang Zhang, Boyang Li
Deep neural networks for video action recognition easily learn to utilize shortcut static features, such as background and objects instead of motion features.
no code implementations • 19 Oct 2022 • YuAn Liu, Lixuan Cao, Bin Wu
We extrapolate from the linear imitation function to general imitation function, which can be non-linear.
3 code implementations • 20 Aug 2022 • Jun Zhang, Sirui Liu, Mengyun Chen, Haotian Chu, Min Wang, Zidong Wang, Jialiang Yu, Ningxi Ni, Fan Yu, Diqing Chen, Yi Isaac Yang, Boxin Xue, Lijiang Yang, YuAn Liu, Yi Qin Gao
Data-driven predictive methods which can efficiently and accurately transform protein sequences into biologically active structures are highly valuable for scientific research and therapeutical development.
no code implementations • 21 Jul 2022 • Alexander Brown, Nenad Tomasev, Jan Freyberg, YuAn Liu, Alan Karthikesalingam, Jessica Schrouff
Machine learning (ML) holds great promise for improving healthcare, but it is critical to ensure that its use will not propagate or amplify health disparities.
no code implementations • 10 Jul 2022 • Peng Wang, YuAn Liu, Guying Lin, Jiatao Gu, Lingjie Liu, Taku Komura, Wenping Wang
ProLiF encodes a 4D light field, which allows rendering a large batch of rays in one training step for image- or patch-level losses.
4 code implementations • 24 Jun 2022 • Sirui Liu, Jun Zhang, Haotian Chu, Min Wang, Boxin Xue, Ningxi Ni, Jialiang Yu, Yuhao Xie, Zhenyu Chen, Mengyun Chen, YuAn Liu, Piya Patra, Fan Xu, Jie Chen, Zidong Wang, Lijiang Yang, Fan Yu, Lei Chen, Yi Qin Gao
We provide in addition the benchmark training procedure for SOTA protein structure prediction model on this dataset.
1 code implementation • 19 May 2022 • Shekoofeh Azizi, Laura Culp, Jan Freyberg, Basil Mustafa, Sebastien Baur, Simon Kornblith, Ting Chen, Patricia MacWilliams, S. Sara Mahdavi, Ellery Wulczyn, Boris Babenko, Megan Wilson, Aaron Loh, Po-Hsuan Cameron Chen, YuAn Liu, Pinal Bavishi, Scott Mayer McKinney, Jim Winkens, Abhijit Guha Roy, Zach Beaver, Fiona Ryan, Justin Krogue, Mozziyar Etemadi, Umesh Telang, Yun Liu, Lily Peng, Greg S. Corrado, Dale R. Webster, David Fleet, Geoffrey Hinton, Neil Houlsby, Alan Karthikesalingam, Mohammad Norouzi, Vivek Natarajan
These results suggest that REMEDIS can significantly accelerate the life-cycle of medical imaging AI development thereby presenting an important step forward for medical imaging AI to deliver broad impact.
1 code implementation • 22 Apr 2022 • YuAn Liu, Yilin Wen, Sida Peng, Cheng Lin, Xiaoxiao Long, Taku Komura, Wenping Wang
In this paper, we present a generalizable model-free 6-DoF object pose estimator called Gen6D.
no code implementations • 9 Mar 2022 • YuAn Liu, Omid Ardakanian, Ioanis Nikolaidis, Hao Liang
With the large scale penetration of electric vehicles (EVs) and the advent of bidirectional chargers, EV aggregators will become a major player in the voltage regulation market.
no code implementations • 2 Feb 2022 • Jessica Schrouff, Natalie Harris, Oluwasanmi Koyejo, Ibrahim Alabdulmohsin, Eva Schnider, Krista Opsahl-Ong, Alex Brown, Subhrajit Roy, Diana Mincu, Christina Chen, Awa Dieng, YuAn Liu, Vivek Natarajan, Alan Karthikesalingam, Katherine Heller, Silvia Chiappa, Alexander D'Amour
Diagnosing and mitigating changes in model fairness under distribution shift is an important component of the safe deployment of machine learning in healthcare settings.
no code implementations • 29 Jan 2022 • Fei Gao, Peng Geng, Jiaqi Guo, YuAn Liu, Dingfeng Guo, Yabo Su, Jie zhou, Xiao Wei, Jin Li, Xu Liu
We introduce ApolloRL, an open platform for research in reinforcement learning for autonomous driving.
no code implementations • 5 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.
1 code implementation • 1 Sep 2021 • Haiping Wang, YuAn Liu, Zhen Dong, Wenping Wang
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.
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.
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.
Ranked #4 on
Surface Normals Estimation
on PCPNet
no code implementations • 12 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.
1 code implementation • CVPR 2022 • YuAn Liu, Sida Peng, Lingjie Liu, Qianqian Wang, Peng Wang, Christian Theobalt, Xiaowei Zhou, Wenping Wang
On such a 3D point, these generalization methods will include inconsistent image features from invisible views, which interfere with the radiance field construction.
4 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.
no code implementations • 8 Apr 2021 • Abhijit Guha Roy, Jie Ren, Shekoofeh Azizi, Aaron Loh, Vivek Natarajan, Basil Mustafa, Nick Pawlowski, Jan Freyberg, YuAn Liu, Zach Beaver, Nam Vo, Peggy Bui, Samantha Winter, Patricia MacWilliams, Greg S. Corrado, Umesh Telang, Yun Liu, Taylan Cemgil, Alan Karthikesalingam, Balaji Lakshminarayanan, Jim Winkens
We develop and rigorously evaluate a deep learning based system that can accurately classify skin conditions while detecting rare conditions for which there is not enough data available for training a confident classifier.
1 code implementation • CVPR 2021 • YuAn Liu, Jingyuan Chen, Zhenfang Chen, Bing Deng, Jianqiang Huang, Hanwang Zhang
The key challenge is how to distinguish the action of interest segments from the background, which is unlabelled even on the video-level.
Weakly-supervised Temporal Action Localization
Weakly Supervised Temporal Action Localization
no code implementations • 14 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
no code implementations • 14 Jan 2021 • Basil Mustafa, Aaron Loh, Jan Freyberg, Patricia MacWilliams, Megan Wilson, Scott Mayer McKinney, Marcin Sieniek, Jim Winkens, YuAn Liu, Peggy Bui, Shruthi Prabhakara, Umesh Telang, Alan Karthikesalingam, Neil Houlsby, Vivek Natarajan
However, for medical imaging, the value of transfer learning is less clear.
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.
1 code implementation • CVPR 2021 • Cheng Lin, Changjian Li, YuAn Liu, Nenglun Chen, Yi-King Choi, Wenping Wang
We introduce Point2Skeleton, an unsupervised method to learn skeletal representations from point clouds.
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.
no code implementations • 15 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.
no code implementations • 9 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.
no code implementations • 22 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.
1 code implementation • 26 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.
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.
no code implementations • 11 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).
no code implementations • 20 Aug 2019 • Yuan Liu, Zhongwei Cheng, Jie Liu, Bourhan Yassin, Zhe Nan, Jiebo Luo
Saving rainforests is a key to halting adverse climate changes.
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.
Ranked #2 on
Action Recognition
on THUMOS’14
no code implementations • 18 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.
no code implementations • 25 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.
no code implementations • 12 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.