no code implementations • 27 May 2024 • Jian Zhao, Lei Jin, Jianshu Li, Zheng Zhu, Yinglei Teng, Jiaojiao Zhao, Sadaf Gulshad, Zheng Wang, Bo Zhao, Xiangbo Shu, Yunchao Wei, Xuecheng Nie, Xiaojie Jin, Xiaodan Liang, Shin'ichi Satoh, Yandong Guo, Cewu Lu, Junliang Xing, Jane Shen Shengmei
The SkatingVerse Workshop & Challenge aims to encourage research in developing novel and accurate methods for human action understanding.
no code implementations • 7 May 2024 • Chen Min, Dawei Zhao, Liang Xiao, Jian Zhao, Xinli Xu, Zheng Zhu, Lei Jin, Jianshu Li, Yulan Guo, Junliang Xing, Liping Jing, Yiming Nie, Bin Dai
In this paper, we address this challenge by introducing a world model-based autonomous driving 4D representation learning framework, dubbed \emph{DriveWorld}, which is capable of pre-training from multi-camera driving videos in a spatio-temporal fashion.
no code implementations • 14 Mar 2024 • Yinggui Wang, Yuanqing Huang, Jianshu Li, Le Yang, Kai Song, Lei Wang
Specifically, face images are masked in the frequency domain using an adaptive MixUp strategy.
no code implementations • 11 Jan 2024 • Xijun Li, Fangzhou Zhu, Hui-Ling Zhen, Weilin Luo, Meng Lu, Yimin Huang, Zhenan Fan, Zirui Zhou, Yufei Kuang, Zhihai Wang, Zijie Geng, Yang Li, Haoyang Liu, Zhiwu An, Muming Yang, Jianshu Li, Jie Wang, Junchi Yan, Defeng Sun, Tao Zhong, Yong Zhang, Jia Zeng, Mingxuan Yuan, Jianye Hao, Jun Yao, Kun Mao
To this end, we present a comprehensive study on the integration of machine learning (ML) techniques into Huawei Cloud's OptVerse AI Solver, which aims to mitigate the scarcity of real-world mathematical programming instances, and to surpass the capabilities of traditional optimization techniques.
1 code implementation • 24 Oct 2023 • Xiaojun Jia, Jianshu Li, Jindong Gu, Yang Bai, Xiaochun Cao
Besides, we provide theoretical analysis to show the model robustness can be improved by the single-step adversarial training with sampled subnetworks.
1 code implementation • ICCV 2023 • Wentong Li, Yuqian Yuan, Song Wang, Jianke Zhu, Jianshu Li, Jian Liu, Lei Zhang
Weakly-supervised image segmentation has recently attracted increasing research attentions, aiming to avoid the expensive pixel-wise labeling.
no code implementations • 27 Jul 2022 • Jianshu Li, Man Luo, Jian Liu, Tao Chen, Chengjie Wang, Ziwei Liu, Shuo Liu, Kewei Yang, Xuning Shao, Kang Chen, Boyuan Liu, Mingyu Guo, Ying Guo, Yingying Ao, Pengfei Gao
In this paper, we present the solutions from the Top 3 teams, in order to boost the research work in the field of image forgery detection.
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.
no code implementations • 13 Feb 2019 • Jian Zhao, Jianshu Li, Xiaoguang Tu, Fang Zhao, Yuan Xin, Junliang Xing, Hengzhu Liu, Shuicheng Yan, Jiashi Feng
In this paper, we study the challenging unconstrained set-based face recognition problem where each subject face is instantiated by a set of media (images and videos) instead of a single image.
1 code implementation • 17 Jan 2019 • Xiaoguang Tu, Jian Zhao, Mei Xie, Guodong Du, Hengsheng Zhang, Jianshu Li, Zheng Ma, Jiashi Feng
Face anti-spoofing (a. k. a presentation attack detection) has drawn growing attention due to the high-security demand in face authentication systems.
Ranked #2 on Face Anti-Spoofing on MSU-MFSD
2 code implementations • NeurIPS 2018 • Yunpeng Chen, Yannis Kalantidis, Jianshu Li, Shuicheng Yan, Jiashi Feng
Learning to capture long-range relations is fundamental to image/video recognition.
no code implementations • 27 Oct 2018 • Yunpeng Chen, Yannis Kalantidis, Jianshu Li, Shuicheng Yan, Jiashi Feng
Learning to capture long-range relations is fundamental to image/video recognition.
Ranked #35 on Action Recognition on UCF101
1 code implementation • 2 Sep 2018 • Jian Zhao, Yu Cheng, Yi Cheng, Yang Yang, Haochong Lan, Fang Zhao, Lin Xiong, Yan Xu, Jianshu Li, Sugiri Pranata, ShengMei Shen, Junliang Xing, Hengzhu Liu, Shuicheng Yan, Jiashi Feng
Benchmarking our model on one of the most popular unconstrained face recognition datasets IJB-C additionally verifies the promising generalizability of AIM in recognizing faces in the wild.
Ranked #1 on Age-Invariant Face Recognition on MORPH Album2
no code implementations • ECCV 2018 • Yunpeng Chen, Yannis Kalantidis, Jianshu Li, Shuicheng Yan, Jiashi Feng
In this paper, we aim to reduce the computational cost of spatio-temporal deep neural networks, making them run as fast as their 2D counterparts while preserving state-of-the-art accuracy on video recognition benchmarks.
Ranked #36 on Action Recognition on UCF101 (using extra training data)
no code implementations • 16 Jul 2018 • Li Zhou, Jian Zhao, Jianshu Li, Li Yuan, Jiashi Feng
Detecting the relations among objects, such as "cat on sofa" and "person ride horse", is a crucial task in image understanding, and beneficial to bridging the semantic gap between images and natural language.
no code implementations • CVPR 2018 • Fang Zhao, Jianshu Li, Jian Zhao, Jiashi Feng
In this paper, we propose a novel weakly supervised model, Multi-scale Anchored Transformer Network (MATN), to accurately localize free-form textual phrases with only image-level supervision.
no code implementations • CVPR 2018 • Jian Zhao, Yu Cheng, Yan Xu, Lin Xiong, Jianshu Li, Fang Zhao, Karlekar Jayashree, Sugiri Pranata, ShengMei Shen, Junliang Xing, Shuicheng Yan, Jiashi Feng
To this end, we propose a Pose Invariant Model (PIM) for face recognition in the wild, with three distinct novelties.
2 code implementations • 10 Apr 2018 • Jian Zhao, Jianshu Li, Yu Cheng, Li Zhou, Terence Sim, Shuicheng Yan, Jiashi Feng
Despite the noticeable progress in perceptual tasks like detection, instance segmentation and human parsing, computers still perform unsatisfactorily on visually understanding humans in crowded scenes, such as group behavior analysis, person re-identification and autonomous driving, etc.
Ranked #1 on Multi-Human Parsing on PASCAL-Part
no code implementations • 8 Dec 2017 • Yunpeng Chen, Jianshu Li, Bin Zhou, Jiashi Feng, Shuicheng Yan
For 320x320 input of batch size = 8, WeaveNet reaches 79. 5% mAP on PASCAL VOC 2007 test in 101 fps with only 4 fps extra cost, and further improves to 79. 7% mAP with more iterations.
no code implementations • NeurIPS 2017 • Jian Zhao, Lin Xiong, Panasonic Karlekar Jayashree, Jianshu Li, Fang Zhao, Zhecan Wang, Panasonic Sugiri Pranata, Panasonic Shengmei Shen, Shuicheng Yan, Jiashi Feng
In particular, we employ an off-the-shelf 3D face model as a simulator to generate profile face images with varying poses.
Ranked #1 on Face Verification on IJB-A
no code implementations • 16 Nov 2017 • Jianshu Li, Shengtao Xiao, Fang Zhao, Jian Zhao, Jianan Li, Jiashi Feng, Shuicheng Yan, Terence Sim
Specifically, iFAN achieves an overall F-score of 91. 15% on the Helen dataset for face parsing, a normalized mean error of 5. 81% on the MTFL dataset for facial landmark localization and an accuracy of 45. 73% on the BNU dataset for emotion recognition with a single model.
2 code implementations • 19 May 2017 • Jianshu Li, Jian Zhao, Yunchao Wei, Congyan Lang, Yidong Li, Terence Sim, Shuicheng Yan, Jiashi Feng
To address the multi-human parsing problem, we introduce a new multi-human parsing (MHP) dataset and a novel multi-human parsing model named MH-Parser.
Ranked #3 on Multi-Human Parsing on MHP v1.0
no code implementations • 18 Aug 2016 • Jianan Li, Xiaodan Liang, Jianshu Li, Tingfa Xu, Jiashi Feng, Shuicheng Yan
Most of existing detection pipelines treat object proposals independently and predict bounding box locations and classification scores over them separately.