1 code implementation • EMNLP 2021 • Hoang Nguyen, Dong Nie, Taivanbat Badamdorj, Yujie Liu, Yingying Zhu, Jason Truong, Li Cheng
Our paper aims to automate the generation of medical reports from chest X-ray image inputs, a critical yet time-consuming task for radiologists.
no code implementations • 24 Jan 2024 • Chuan Guo, Yuxuan Mu, Xinxin Zuo, Peng Dai, Youliang Yan, Juwei Lu, Li Cheng
Building upon this, we present a novel generative model that produces diverse stylization results of a single motion (latent) code.
no code implementations • 19 Dec 2023 • Payam Jome Yazdian, Eric Liu, Li Cheng, Angelica Lim
This paper proposes MotionScript, a motion-to-text conversion algorithm and natural language representation for human body motions.
1 code implementation • 29 Nov 2023 • Chuan Guo, Yuxuan Mu, Muhammad Gohar Javed, Sen Wang, Li Cheng
For the base-layer motion tokens, a Masked Transformer is designated to predict randomly masked motion tokens conditioned on text input at training stage.
Ranked #1 on Motion Synthesis on HumanML3D
1 code implementation • 22 Nov 2023 • Zijian Kuang, Lihang Ying, Shi Jin, Li Cheng
To address this challenge, we propose the combination of two-stage supervised and self-supervised training to address the challenge of obtaining animal cooperation for 3D scanning.
1 code implementation • 12 Apr 2023 • Wei Ji, Jingjing Li, Qi Bi, TingWei Liu, Wenbo Li, Li Cheng
Recently, Meta AI Research approaches a general, promptable Segment Anything Model (SAM) pre-trained on an unprecedentedly large segmentation dataset (SA-1B).
1 code implementation • 16 Mar 2023 • Shihao Zou, Yuxuan Mu, Xinxin Zuo, Sen Wang, Li Cheng
Motivated by the above mentioned issues, we present in this paper a dedicated end-to-end sparse deep learning approach for event-based pose tracking: 1) to our knowledge this is the first time that 3D human pose tracking is obtained from events only, thus eliminating the need of accessing to any frame-based images as part of input; 2) our approach is based entirely upon the framework of Spiking Neural Networks (SNNs), which consists of Spike-Element-Wise (SEW) ResNet and a novel Spiking Spatiotemporal Transformer; 3) a large-scale synthetic dataset is constructed that features a broad and diverse set of annotated 3D human motions, as well as longer hours of event stream data, named SynEventHPD.
1 code implementation • CVPR 2023 • Wei Ji, Jingjing Li, Cheng Bian, Zongwei Zhou, Jiaying Zhao, Alan L. Yuille, Li Cheng
This gives rise to significantly more robust segmentation of image objects in complex scenes and under adverse conditions.
1 code implementation • 9 Jul 2022 • Shihao Zou, Yuanlu Xu, Chao Li, Lingni Ma, Li Cheng, Minh Vo
In this paper, we propose Snipper, a unified framework to perform multi-person 3D pose estimation, tracking, and motion forecasting simultaneously in a single stage.
1 code implementation • 4 Jul 2022 • Chuan Guo, Xinxin Zuo, Sen Wang, Li Cheng
Our approach is flexible, could be used for both text2motion and motion2text tasks.
Ranked #3 on Motion Captioning on HumanML3D
1 code implementation • ICLR 2022 • Wei Ji, Jingjing Li, Qi Bi, Chuan Guo, Jie Liu, Li Cheng
The laborious and time-consuming manual annotation has become a real bottleneck in various practical scenarios.
no code implementations • 28 Jan 2022 • Shuang Wu, Zhenguang Li, Shijian Lu, Li Cheng
Music and dance have always co-existed as pillars of human activities, contributing immensely to the cultural, social, and entertainment functions in virtually all societies.
no code implementations • CVPR 2022 • Jingjing Li, Tianyu Yang, Wei Ji, Jue Wang, Li Cheng
Inspired by recent success in unsupervised contrastive representation learning, we propose a novel denoised cross-video contrastive algorithm, aiming to enhance the feature discrimination ability of video snippets for accurate temporal action localization in the weakly-supervised setting.
no code implementations • CVPR 2022 • Taivanbat Badamdorj, Mrigank Rochan, Yang Wang, Li Cheng
Our framework encodes a video into a vector representation by learning to pick video clips that help to distinguish it from other videos via a contrastive objective using dropout noise.
1 code implementation • CVPR 2022 • Chuan Guo, Shihao Zou, Xinxin Zuo, Sen Wang, Wei Ji, Xingyu Li, Li Cheng
Automated generation of 3D human motions from text is a challenging problem.
Ranked #6 on Motion Synthesis on InterHuman
1 code implementation • 30 Dec 2021 • Zhenguang Liu, Shuang Wu, Shuyuan Jin, Shouling Ji, Qi Liu, Shijian Lu, Li Cheng
One aspect that has been obviated so far, is the fact that how we represent the skeletal pose has a critical impact on the prediction results.
no code implementations • 3 Dec 2021 • Shuang Wu, Shijian Lu, Li Cheng
We introduce an optimal transport distance for evaluating the authenticity of the generated dance distribution and a Gromov-Wasserstein distance to measure the correspondence between the dance distribution and the input music.
1 code implementation • NeurIPS 2021 • Jingjing Li, Wei Ji, Qi Bi, Cheng Yan, Miao Zhang, Yongri Piao, Huchuan Lu, Li Cheng
As a by-product, a CapS dataset is constructed by augmenting existing benchmark training set with additional image tags and captions.
no code implementations • 26 Nov 2021 • Ji Yang, Youdong Ma, Xinxin Zuo, Sen Wang, Minglun Gong, Li Cheng
This paper considers to jointly tackle the highly correlated tasks of estimating 3D human body poses and predicting future 3D motions from RGB image sequences.
no code implementations • 23 Nov 2021 • Xingzheng Lyu, Li Cheng, Sanyuan Zhang
Topological and geometrical analysis of retinal blood vessel is a cost-effective way for early detection of many common diseases.
no code implementations • 12 Nov 2021 • Chuan Guo, Xinxin Zuo, Sen Wang, Xinshuang Liu, Shihao Zou, Minglun Gong, Li Cheng
Action2motion stochastically generates plausible 3D pose sequences of a prescribed action category, which are processed and rendered by motion2video to form 2D videos.
1 code implementation • 27 Aug 2021 • Hoang T. N. Nguyen, Dong Nie, Taivanbat Badamdorj, Yujie Liu, Yingying Zhu, Jason Truong, Li Cheng
Our paper focuses on automating the generation of medical reports from chest X-ray image inputs, a critical yet time-consuming task for radiologists.
1 code implementation • 15 Aug 2021 • Shihao Zou, Xinxin Zuo, Sen Wang, Yiming Qian, Chuan Guo, Li Cheng
This paper focuses on a new problem of estimating human pose and shape from single polarization images.
1 code implementation • ICCV 2021 • Shihao Zou, Chuan Guo, Xinxin Zuo, Sen Wang, Pengyu Wang, Xiaoqin Hu, Shoushun Chen, Minglun Gong, Li Cheng
Event camera is an emerging imaging sensor for capturing dynamics of moving objects as events, which motivates our work in estimating 3D human pose and shape from the event signals.
no code implementations • 5 Aug 2021 • Ji Yang, Xinxin Zuo, Sen Wang, Zhenbo Yu, Xingyu Li, Bingbing Ni, Minglun Gong, Li Cheng
A dataset of generic 3D objects with ground-truth annotated skeletons is collected.
1 code implementation • 15 Jul 2021 • Xinxin Zuo, Sen Wang, Qiang Sun, Minglun Gong, Li Cheng
However, Chamfer distance is quite sensitive to noise and outliers, thus could be unreliable to assign correspondences.
1 code implementation • 2 Jul 2021 • Seyed Mojtaba Marvasti-Zadeh, Javad Khaghani, Li Cheng, Hossein Ghanei-Yakhdan, Shohreh Kasaei
A strong visual object tracker nowadays relies on its well-crafted modules, which typically consist of manually-designed network architectures to deliver high-quality tracking results.
1 code implementation • CVPR 2021 • Wei Ji, Jingjing Li, Shuang Yu, Miao Zhang, Yongri Piao, Shunyu Yao, Qi Bi, Kai Ma, Yefeng Zheng, Huchuan Lu, Li Cheng
Complex backgrounds and similar appearances between objects and their surroundings are generally recognized as challenging scenarios in Salient Object Detection (SOD).
Ranked #13 on Thermal Image Segmentation on RGB-T-Glass-Segmentation
1 code implementation • CVPR 2021 • Wei Ji, Shuang Yu, Junde Wu, Kai Ma, Cheng Bian, Qi Bi, Jingjing Li, Hanruo Liu, Li Cheng, Yefeng Zheng
To our knowledge, our work is the first in producing calibrated predictions under different expertise levels for medical image segmentation.
no code implementations • ICCV 2021 • Taivanbat Badamdorj, Mrigank Rochan, Yang Wang, Li Cheng
In video highlight detection, the goal is to identify the interesting moments within an unedited video.
no code implementations • 21 Sep 2020 • Jiabo Ma, Sibo Liu, Shenghua Cheng, Xiuli Liu, Li Cheng, Shaoqun Zeng
High-resolution 3D medical images are important for analysis and diagnosis, but axial scanning to acquire them is very time-consuming.
1 code implementation • 30 Jul 2020 • Chuan Guo, Xinxin Zuo, Sen Wang, Shihao Zou, Qingyao Sun, Annan Deng, Minglun Gong, Li Cheng
Action recognition is a relatively established task, where givenan input sequence of human motion, the goal is to predict its ac-tion category.
no code implementations • ECCV 2020 • Shihao Zou, Xinxin Zuo, Yiming Qian, Sen Wang, Chi Xu, Minglun Gong, Li Cheng
Inspired by the recent advances in human shape estimation from single color images, in this paper, we attempt at estimating human body shapes by leveraging the geometric cues from single polarization images.
no code implementations • 5 Jun 2020 • Xinxin Zuo, Sen Wang, Jiangbin Zheng, Weiwei Yu, Minglun Gong, Ruigang Yang, Li Cheng
First, based on a generative human template, for every two frames having sufficient overlap, an initial pairwise alignment is performed; It is followed by a global non-rigid registration procedure, in which partial results from RGBD frames are collected into a unified 3D shape, under the guidance of correspondences from the pairwise alignment; Finally, the texture map of the reconstructed human model is optimized to deliver a clear and spatially consistent texture.
no code implementations • 4 Jun 2020 • Seyed Mojtaba Marvasti-Zadeh, Javad Khaghani, Hossein Ghanei-Yakhdan, Shohreh Kasaei, Li Cheng
To address this problem, we introduce a context-aware IoU-guided tracker (COMET) that exploits a multitask two-stream network and an offline reference proposal generation strategy.
no code implementations • 30 Apr 2020 • Shihao Zou, Xinxin Zuo, Yiming Qian, Sen Wang, Chuan Guo, Chi Xu, Minglun Gong, Li Cheng
Polarization images are known to be able to capture polarized reflected lights that preserve rich geometric cues of an object, which has motivated its recent applications in reconstructing detailed surface normal of the objects of interest.
no code implementations • 22 Apr 2020 • Dong Wang, Xiaoqian Qin, Fengyi Song, Li Cheng
Generative adversarial networks (GANs), famous for the capability of learning complex underlying data distribution, are however known to be tricky in the training process, which would probably result in mode collapse or performance deterioration.
no code implementations • 15 Jan 2020 • Li Cheng, Yijie Wang, Xinwang Liu, Bin Li
Existing methods usually perform feature selection and outlier scoring separately, which would select feature subsets that may not optimally serve for outlier detection, leading to unsatisfying performance.
no code implementations • 27 Dec 2019 • Mingxin Zhao, Li Cheng, Xu Yang, Peng Feng, Liyuan Liu, Nanjian Wu
Meanwhile, we propose a joint loss function and a training method.
1 code implementation • 2 Dec 2019 • Seyed Mojtaba Marvasti-Zadeh, Li Cheng, Hossein Ghanei-Yakhdan, Shohreh Kasaei
Second, popular visual tracking benchmarks and their respective properties are compared, and their evaluation metrics are summarized.
1 code implementation • 12 Nov 2019 • Tianfu Li, Zhibin Zhao, Chuang Sun, Li Cheng, Xuefeng Chen, Ruqiang Yan, Robert X. Gao
In this paper, a novel wavelet driven deep neural network termed as WaveletKernelNet (WKN) is presented, where a continuous wavelet convolutional (CWConv) layer is designed to replace the first convolutional layer of the standard CNN.
no code implementations • 12 Dec 2018 • Agarwal Aman, Zaitsev Ivan, Wang Xuanhui, Li Cheng, Najork Marc, Joachims Thorsten
Presentation bias is one of the key challenges when learning from implicit feedback in search engines, as it confounds the relevance signal.
no code implementations • 11 Oct 2018 • Agarwal Aman, Wang Xuanhui, Li Cheng, Bendersky Michael, Najork Marc
In this paper, we study how to improve the data efficiency of IPS approaches in the offline comparison setting.
no code implementations • 1 Sep 2017 • Xiaowei Zhang, Li Cheng, Bo Li, Hai-Miao Hu
A major bottleneck of pedestrian detection lies on the sharp performance deterioration in the presence of small-size pedestrians that are relatively far from the camera.
1 code implementation • 7 Jun 2017 • He Zhao, Huiqi Li, Li Cheng
This paper aims at synthesizing filamentary structured images such as retinal fundus images and neuronal images, as follows: Given a ground-truth, to generate multiple realistic looking phantoms.
no code implementations • 26 Mar 2017 • Xiaowei Zhang, Xudong Shi, Yu Sun, Li Cheng
Our model first takes a correction step on the grossly corrupted responses via geodesic curves on the manifold, and then performs multivariate linear regression on the corrected data.
no code implementations • 11 Jan 2017 • Xiaowei Zhang, Chi Xu, Yu Zhang, Tingshao Zhu, Li Cheng
The implementation of our approach and comparison methods as well as the involved datasets are made publicly available in support of the open-source and reproducible research initiatives.
no code implementations • 4 Jan 2017 • Li Liu, Yongzhong Yang, Lakshmi Narasimhan Govindarajan, Shu Wang, Bin Hu, Li Cheng, David S. Rosenblum
We propose in this paper an atomic action-based Bayesian model that constructs Allen's interval relation networks to characterize complex activities with structural varieties in a probabilistic generative way: By introducing latent variables from the Chinese restaurant process, our approach is able to capture all possible styles of a particular complex activity as a unique set of distributions over atomic actions and relations.
no code implementations • 2 Dec 2016 • Yu Zhang, Chi Xu, Li Cheng
This paper focuses on the challenging problem of 3D pose estimation of a diverse spectrum of articulated objects from single depth images.
no code implementations • 13 Sep 2016 • Chi Xu, Lakshmi Narasimhan Govindarajan, Yu Zhang, Li Cheng
Pose estimation, tracking, and action recognition of articulated objects from depth images are important and challenging problems, which are normally considered separately.
no code implementations • 7 Jun 2016 • Chi Xu, Lakshmi Narasimhan Govindarajan, Li Cheng
Detecting hand actions from ego-centric depth sequences is a practically challenging problem, owing mostly to the complex and dexterous nature of hand articulations as well as non-stationary camera motion.
no code implementations • ICCV 2015 • Lin Gu, Li Cheng
Step one of our approach centers on a data-driven latent classification tree model to detect the filamentary fragments.
no code implementations • 24 Nov 2015 • Ashwin Nanjappa, Li Cheng, Wei Gao, Chi Xu, Adam Claridge-Chang, Zoe Bichler
We focus on the challenging problem of efficient mouse 3D pose estimation based on static images, and especially single depth images.
no code implementations • 19 Feb 2014 • Jaydeep De, Xiaowei Zhang, Li Cheng
In this paper we consider the problem of graph-based transductive classification, and we are particularly interested in the directed graph scenario which is a natural form for many real world applications.