no code implementations • 19 May 2022 • Shuo Yang, Zeke Xie, Hanyu Peng, Min Xu, Mingming Sun, Ping Li
To answer these, we propose dataset pruning, an optimization-based sample selection method that can (1) examine the influence of removing a particular set of training samples on model's generalization ability with theoretical guarantee, and (2) construct a smallest subset of training data that yields strictly constrained generalization gap.
no code implementations • 12 May 2022 • Shuo Yang, Xinxiao wu
Language-driven action localization in videos is a challenging task that involves not only visual-linguistic matching but also action boundary prediction.
no code implementations • 12 May 2022 • Yue Zhao, Yantao Shen, Yuanjun Xiong, Shuo Yang, Wei Xia, Zhuowen Tu, Bernt Schiele, Stefano Soatto
We present a method to train a classification system that achieves paragon performance in both error rate and NFR, at the inference cost of a single model.
no code implementations • 30 Apr 2022 • Kai Wang, Xiangyu Peng, Shuo Yang, Jianfei Yang, Zheng Zhu, Xinchao Wang, Yang You
This paradigm, however, is prone to significant degeneration under heavy label noise, as the number of clean samples is too small for conventional methods to behave well.
1 code implementation • 3 Mar 2022 • Kai Wang, Bo Zhao, Xiangyu Peng, Zheng Zhu, Shuo Yang, Shuo Wang, Guan Huang, Hakan Bilen, Xinchao Wang, Yang You
Dataset condensation aims at reducing the network training effort through condensing a cumbersome training set into a compact synthetic one.
1 code implementation • 1 Mar 2022 • Qian Zhao, Shuo Yang, Binbin Hu, Zhiqiang Zhang, Yakun Wang, Yusong Chen, Jun Zhou, Chuan Shi
Temporal link prediction, as one of the most crucial work in temporal graphs, has attracted lots of attention from the research area.
no code implementations • 24 Feb 2022 • Shuo Yang, Yijun Dong, Rachel Ward, Inderjit S. Dhillon, Sujay Sanghavi, Qi Lei
Data augmentation is popular in the training of large neural networks; currently, however, there is no clear theoretical comparison between different algorithmic choices on how to use augmented data.
1 code implementation • 13 Dec 2021 • Dong Liang, Ling Li, Mingqiang Wei, Shuo Yang, Liyan Zhang, Wenhan Yang, Yun Du, Huiyu Zhou
Low-light image enhancement (LLE) remains challenging due to the unfavorable prevailing low-contrast and weak-visibility problems of single RGB images.
1 code implementation • 2 Dec 2021 • Ju He, Shuo Yang, Shaokang Yang, Adam Kortylewski, Xiaoding Yuan, Jie-Neng Chen, Shuai Liu, Cheng Yang, Qihang Yu, Alan Yuille
To help address this problem, we propose PartImageNet, a large, high-quality dataset with part segmentation annotations.
no code implementations • NeurIPS 2021 • Zhao Song, Shuo Yang, Ruizhe Zhang
The classical training method requires paying $\Omega(mnd)$ cost for both forward computation and backward computation, where $m$ is the width of the neural network, and we are given $n$ training points in $d$-dimensional space.
no code implementations • 8 Oct 2021 • Shuo Yang, Le Hou, Xiaodan Song, Qiang Liu, Denny Zhou
Our approach exploits the special structure of BERT that contains a stack of repeated modules (i. e., transformer encoders).
no code implementations • ICLR 2022 • Shuo Yang, Peize Sun, Yi Jiang, Xiaobo Xia, Ruiheng Zhang, Zehuan Yuan, Changhu Wang, Ping Luo, Min Xu
A more realistic object detection paradigm, Open-World Object Detection, has arisen increasing research interests in the community recently.
no code implementations • 29 Sep 2021 • Shuo Yang, Yijun Dong, Rachel Ward, Inderjit S Dhillon, Sujay Sanghavi, Qi Lei
Data augmentation is popular in the training of large neural networks; currently, however, there is no clear theoretical comparison between different algorithmic choices on how to use augmented data.
no code implementations • 6 Jul 2021 • Wei Li, Yuanjun Xiong, Shuo Yang, Mingze Xu, Yongxin Wang, Wei Xia
We design a new instance-to-track matching objective to learn appearance embedding that compares a candidate detection to the embedding of the tracks persisted in the tracker.
no code implementations • 27 May 2021 • Shuo Yang, Erkun Yang, Bo Han, Yang Liu, Min Xu, Gang Niu, Tongliang Liu
Traditionally, the transition from clean distribution to noisy distribution (i. e., clean label transition matrix) has been widely exploited to learn a clean label classifier by employing the noisy data.
no code implementations • CVPR 2021 • Rahul Duggal, Hao Zhou, Shuo Yang, Yuanjun Xiong, Wei Xia, Zhuowen Tu, Stefano Soatto
Existing systems use the same embedding model to compute representations (embeddings) for the query and gallery images.
no code implementations • 13 Mar 2021 • Jiahao Xia, Haimin Zhang, Shiping Wen, Shuo Yang, Min Xu
Moreover, we generate a cheap heatmap based on the face alignment result and fuse it with features to improve the performance of the other two tasks.
no code implementations • 3 Mar 2021 • Shuo Yang, Tongzheng Ren, Sanjay Shakkottai, Eric Price, Inderjit S. Dhillon, Sujay Sanghavi
We propose to accelerate existing linear bandit algorithms to achieve per-step time complexity sublinear in the number of arms $K$.
no code implementations • 3 Mar 2021 • Shuo Yang, Tongzheng Ren, Inderjit S. Dhillon, Sujay Sanghavi
Specifically, we focus on a challenging setting where 1) the reward distribution of an arm depends on the set $s$ it is part of, and crucially 2) there is \textit{no total order} for the arms in $\mathcal{A}$.
1 code implementation • 25 Feb 2021 • Yuanhan Zhang, Zhenfei Yin, Jing Shao, Ziwei Liu, Shuo Yang, Yuanjun Xiong, Wei Xia, Yan Xu, Man Luo, Jian Liu, Jianshu Li, Zhijun Chen, Mingyu Guo, Hui Li, Junfu Liu, Pengfei Gao, Tianqi Hong, Hao Han, Shijie Liu, Xinhua Chen, Di Qiu, Cheng Zhen, Dashuang Liang, Yufeng Jin, Zhanlong Hao
It is the largest face anti-spoofing dataset in terms of the numbers of the data and the subjects.
2 code implementations • 18 Feb 2021 • Liming Jiang, Zhengkui Guo, Wayne Wu, Zhaoyang Liu, Ziwei Liu, Chen Change Loy, Shuo Yang, Yuanjun Xiong, Wei Xia, Baoying Chen, Peiyu Zhuang, Sili Li, Shen Chen, Taiping Yao, Shouhong Ding, Jilin Li, Feiyue Huang, Liujuan Cao, Rongrong Ji, Changlei Lu, Ganchao Tan
This paper reports methods and results in the DeeperForensics Challenge 2020 on real-world face forgery detection.
no code implementations • IWSLT (ACL) 2022 • Di wu, Liang Ding, Shuo Yang, Mingyang Li
Recently, the performance of the neural word alignment models has exceeded that of statistical models.
2 code implementations • ICLR 2021 • Shuo Yang, Lu Liu, Min Xu
In this paper, we calibrate the distribution of these few-sample classes by transferring statistics from the classes with sufficient examples, then an adequate number of examples can be sampled from the calibrated distribution to expand the inputs to the classifier.
no code implementations • 1 Jan 2021 • Shuo Yang, Le Hou, Xiaodan Song, Qiang Liu, Denny Zhou
It has been widely observed that increasing deep learning model sizes often leads to significant performance improvements on a variety of natural language processing and computer vision tasks.
no code implementations • 1 Jan 2021 • Di wu, Liang Ding, Shuo Yang, DaCheng Tao
Recently, the performance of the neural word alignment models has exceeded that of statistical models.
no code implementations • 31 Dec 2020 • Jian-Hao Zhang, Shuo Yang, Yang Qi, Zheng-Cheng Gu
The construction and classification of crystalline symmetry protected topological (SPT) phases in interacting bosonic and fermionic systems have been intensively studied in the past few years.
Strongly Correlated Electrons Mesoscale and Nanoscale Physics Mathematical Physics Mathematical Physics
no code implementations • 24 Nov 2020 • Thomas Matheson, Carl Stubens, Nicholas Wolf, Chien-Hsiu Lee, Gautham Narayan, Abhijit Saha, Adam Scott, Monika Soraisam, Adam S. Bolton, Benjamin Hauger, David R. Silva, John Kececioglu, Carlos Scheidegger, Richard Snodgrass, Patrick D. Aleo, Eric Evans-Jacquez, Navdeep Singh, Zhe Wang, Shuo Yang, Zhenge Zhao
We describe the Arizona-NOIRLab Temporal Analysis and Response to Events System (ANTARES), a software instrument designed to process large-scale streams of astronomical time-domain alerts.
Instrumentation and Methods for Astrophysics
no code implementations • CVPR 2021 • Sijie Yan, Yuanjun Xiong, Kaustav Kundu, Shuo Yang, Siqi Deng, Meng Wang, Wei Xia, Stefano Soatto
Reducing inconsistencies in the behavior of different versions of an AI system can be as important in practice as reducing its overall error.
1 code implementation • 30 Oct 2020 • Wei Li, Yuanjun Xiong, Shuo Yang, Siqi Deng, Wei Xia
We combine this scheme with SSD detectors by proposing a novel tracking anchor assignment module.
2 code implementations • CVPR 2020 • Guan'an Wang, Shuo Yang, Huanyu Liu, Zhicheng Wang, Yang Yang, Shuliang Wang, Gang Yu, Erjin Zhou, Jian Sun
When aligning two groups of local features from two images, we view it as a graph matching problem and propose a cross-graph embedded-alignment (CGEA) layer to jointly learn and embed topology information to local features, and straightly predict similarity score.
no code implementations • 8 Mar 2020 • Shuo Yang, Wei Yu, Ying Zheng, Hongxun Yao, Tao Mei
To solve this new problem, we propose a hierarchical adaptive semantic-visual tree (ASVT) to depict the architecture of merchandise categories, which evaluates semantic similarities between different semantic levels and visual similarities within the same semantic class simultaneously.
no code implementations • CVPR 2021 • Shuo Yang, Min Xu, Haozhe Xie, Stuart Perry, Jiahao Xia
Inspired by this, we propose a novel method, named Mem3D, that explicitly constructs shape priors to supplement the missing information in the image.
no code implementations • NeurIPS 2019 • Shuo Yang, Yanyao Shen, Sujay Sanghavi
In this paper, we provide a new algorithm - Interaction Hard Thresholding (IntHT) which is the first one to provably accurately solve this problem in sub-quadratic time and space.
1 code implementation • ICCV 2019 • Keqiang Sun, Wayne Wu, Tinghao Liu, Shuo Yang, Quan Wang, Qiang Zhou, Zuochang Ye, Chen Qian
A structure predictor is proposed to predict the missing face structural information temporally, which serves as a geometry prior.
no code implementations • 10 Sep 2019 • Shuo Yang, Wei zhang, Weizhi Lu, Hesheng Wang, Yibin Li
However, the general video captioning methods focus more on the understanding of the full frame, lacking of consideration on the specific object of interests in robotic manipulations.
no code implementations • 19 Feb 2019 • Chen Change Loy, Dahua Lin, Wanli Ouyang, Yuanjun Xiong, Shuo Yang, Qingqiu Huang, Dongzhan Zhou, Wei Xia, Quanquan Li, Ping Luo, Junjie Yan, Jian-Feng Wang, Zuoxin Li, Ye Yuan, Boxun Li, Shuai Shao, Gang Yu, Fangyun Wei, Xiang Ming, Dong Chen, Shifeng Zhang, Cheng Chi, Zhen Lei, Stan Z. Li, Hongkai Zhang, Bingpeng Ma, Hong Chang, Shiguang Shan, Xilin Chen, Wu Liu, Boyan Zhou, Huaxiong Li, Peng Cheng, Tao Mei, Artem Kukharenko, Artem Vasenin, Nikolay Sergievskiy, Hua Yang, Liangqi Li, Qiling Xu, Yuan Hong, Lin Chen, Mingjun Sun, Yirong Mao, Shiying Luo, Yongjun Li, Ruiping Wang, Qiaokang Xie, Ziyang Wu, Lei Lu, Yiheng Liu, Wengang Zhou
This paper presents a review of the 2018 WIDER Challenge on Face and Pedestrian.
2 code implementations • CVPR 2019 • Jiaqi Wang, Kai Chen, Shuo Yang, Chen Change Loy, Dahua Lin
State-of-the-art detectors mostly rely on a dense anchoring scheme, where anchors are sampled uniformly over the spatial domain with a predefined set of scales and aspect ratios.
Ranked #1 on
Region Proposal
on COCO test-dev
no code implementations • 2 Nov 2018 • Shuo Yang
It also demonstrates the outstanding performance of these proposed models as well as other state of the art machine learning models when applied to medical research problems and other real-world large-scale systems, reveals the great potential of statistical relational learning for exploring the structured health-related data to facilitate medical research.
no code implementations • ICLR 2018 • Kenny J. Young, Richard S. Sutton, Shuo Yang
We suggest one advantage of this particular type of memory is the ability to easily assign credit to a specific state when remembered information is found to be useful.
2 code implementations • CVPR 2018 • Wayne Wu, Chen Qian, Shuo Yang, Quan Wang, Yici Cai, Qiang Zhou
By utilising boundary information of 300-W dataset, our method achieves 3. 92% mean error with 0. 39% failure rate on COFW dataset, and 1. 25% mean error on AFLW-Full dataset.
Ranked #2 on
Face Alignment
on AFLW-19
(using extra training data)
1 code implementation • CVPR 2018 • Kai Chen, Jiaqi Wang, Shuo Yang, Xingcheng Zhang, Yuanjun Xiong, Chen Change Loy, Dahua Lin
High-performance object detection relies on expensive convolutional networks to compute features, often leading to significant challenges in applications, e. g. those that require detecting objects from video streams in real time.
no code implementations • CVPR 2017 2017 • Wenyan Wu, Shuo Yang
Face alignment is a critical topic in the computer vision community.
Ranked #23 on
Face Alignment
on WFLW
no code implementations • 9 Jun 2017 • Shuo Yang, Yuanjun Xiong, Chen Change Loy, Xiaoou Tang
Specifically, our method achieves 76. 4 average precision on the challenging WIDER FACE dataset and 96% recall rate on the FDDB dataset with 7 frames per second (fps) for 900 * 1300 input image.
14 code implementations • CVPR 2017 • Fei Wang, Mengqing Jiang, Chen Qian, Shuo Yang, Cheng Li, Honggang Zhang, Xiaogang Wang, Xiaoou Tang
In this work, we propose "Residual Attention Network", a convolutional neural network using attention mechanism which can incorporate with state-of-art feed forward network architecture in an end-to-end training fashion.
Ranked #358 on
Image Classification
on ImageNet
no code implementations • 7 Apr 2017 • Xiaoming Deng, Shuo Yang, yinda zhang, Ping Tan, Liang Chang, Hongan Wang
We propose a novel 3D neural network architecture for 3D hand pose estimation from a single depth image.
no code implementations • 29 Jan 2017 • Shuo Yang, Ping Luo, Chen Change Loy, Xiaoou Tang
We propose a deep convolutional neural network (CNN) for face detection leveraging on facial attributes based supervision.
no code implementations • 8 Dec 2016 • Xiaoming Deng, Ye Yuan, Yinda Zhang, Ping Tan, Liang Chang, Shuo Yang, Hongan Wang
Hand detection is essential for many hand related tasks, e. g. parsing hand pose, understanding gesture, which are extremely useful for robotics and human-computer interaction.
no code implementations • 4 Jul 2016 • Shuo Yang, Mohammed Korayem, Khalifeh Aljadda, Trey Grainger, Sriraam Natarajan
In this paper, we proposed a way to adapt the state-of-the-art in SRL learning approaches to construct a real hybrid recommendation system.
1 code implementation • CVPR 2016 • Shuo Yang, Ping Luo, Chen Change Loy, Xiaoou Tang
Face detection is one of the most studied topics in the computer vision community.
Ranked #18 on
Face Detection
on WIDER Face (Medium)
2 code implementations • ICCV 2015 • Shuo Yang, Ping Luo, Chen Change Loy, Xiaoou Tang
In this paper, we propose a novel deep convolutional network (DCN) that achieves outstanding performance on FDDB, PASCAL Face, and AFW.
no code implementations • CVPR 2015 • Wanli Ouyang, Xiaogang Wang, Xingyu Zeng, Shi Qiu, Ping Luo, Yonglong Tian, Hongsheng Li, Shuo Yang, Zhe Wang, Chen-Change Loy, Xiaoou Tang
In this paper, we propose deformable deep convolutional neural networks for generic object detection.
no code implementations • 11 Sep 2014 • Wanli Ouyang, Ping Luo, Xingyu Zeng, Shi Qiu, Yonglong Tian, Hongsheng Li, Shuo Yang, Zhe Wang, Yuanjun Xiong, Chen Qian, Zhenyao Zhu, Ruohui Wang, Chen-Change Loy, Xiaogang Wang, Xiaoou Tang
In the proposed new deep architecture, a new deformation constrained pooling (def-pooling) layer models the deformation of object parts with geometric constraint and penalty.