no code implementations • 19 Apr 2022 • Atsuhiro Noguchi, Xiao Sun, Stephen Lin, Tatsuya Harada
We propose an unsupervised method for 3D geometry-aware representation learning of articulated objects.
no code implementations • 12 Mar 2022 • Zhihang Zhong, Mingdeng Cao, Xiao Sun, Zhirong Wu, Zhongyi Zhou, Yinqiang Zheng, Stephen Lin, Imari Sato
In this paper, instead of two consecutive frames, we propose to exploit a pair of images captured by dual RS cameras with reversed RS directions for this highly challenging task.
no code implementations • 8 Mar 2022 • Yutong Chen, Fangyun Wei, Xiao Sun, Zhirong Wu, Stephen Lin
This simple baseline surpasses the previous state-of-the-art results on two sign language translation benchmarks, demonstrating the effectiveness of transfer learning.
no code implementations • 17 Dec 2021 • Yinghao Xu, Fangyun Wei, Xiao Sun, Ceyuan Yang, Yujun Shen, Bo Dai, Bolei Zhou, Stephen Lin
Typically in recent work, the pseudo-labels are obtained by training a model on the labeled data, and then using confident predictions from the model to teach itself.
1 code implementation • 22 Nov 2021 • Kenneth Li, Xiao Sun, Zhirong Wu, Fangyun Wei, Stephen Lin
For human action understanding, a popular research direction is to analyze short video clips with unambiguous semantic content, such as jumping and drinking.
no code implementations • 29 Sep 2021 • Kenneth Li, Xiao Sun, Zhirong Wu, Fangyun Wei, Stephen Lin
However, methods for understanding short semantic actions cannot be directly translated to long kinematic sequences such as dancing, where it becomes challenging even to semantically label the human movements.
1 code implementation • 9 Sep 2021 • Dong-Jin Kim, Xiao Sun, Jinsoo Choi, Stephen Lin, In So Kweon
A common problem in the task of human-object interaction (HOI) detection is that numerous HOI classes have only a small number of labeled examples, resulting in training sets with a long-tailed distribution.
Ranked #22 on
Human-Object Interaction Detection
on HICO-DET
no code implementations • 27 Aug 2021 • Andrea Fasoli, Chia-Yu Chen, Mauricio Serrano, Xiao Sun, Naigang Wang, Swagath Venkataramani, George Saon, Xiaodong Cui, Brian Kingsbury, Wei zhang, Zoltán Tüske, Kailash Gopalakrishnan
We investigate the impact of aggressive low-precision representations of weights and activations in two families of large LSTM-based architectures for Automatic Speech Recognition (ASR): hybrid Deep Bidirectional LSTM - Hidden Markov Models (DBLSTM-HMMs) and Recurrent Neural Network - Transducers (RNN-Ts).
1 code implementation • ICCV 2021 • Ailing Zeng, Xiao Sun, Lei Yang, Nanxuan Zhao, Minhao Liu, Qiang Xu
While the average prediction accuracy has been improved significantly over the years, the performance on hard poses with depth ambiguity, self-occlusion, and complex or rare poses is still far from satisfactory.
Ranked #6 on
Skeleton Based Action Recognition
on NTU RGB+D 120
1 code implementation • 20 May 2021 • Xiao Sun, Bahador Bahmani, Nikolaos N. Vlassis, WaiChing Sun, Yanxun Xu
This paper presents a computational framework that generates ensemble predictive mechanics models with uncertainty quantification (UQ).
no code implementations • NeurIPS 2020 • Chia-Yu Chen, Jiamin Ni, Songtao Lu, Xiaodong Cui, Pin-Yu Chen, Xiao Sun, Naigang Wang, Swagath Venkataramani, Vijayalakshmi Srinivasan, Wei zhang, Kailash Gopalakrishnan
Large-scale distributed training of Deep Neural Networks (DNNs) on state-of-the-art platforms is expected to be severely communication constrained.
1 code implementation • ICCV 2021 • Atsuhiro Noguchi, Xiao Sun, Stephen Lin, Tatsuya Harada
We present Neural Articulated Radiance Field (NARF), a novel deformable 3D representation for articulated objects learned from images.
no code implementations • NeurIPS 2020 • Xiao Sun, Naigang Wang, Chia-Yu Chen, Jiamin Ni, Ankur Agrawal, Xiaodong Cui, Swagath Venkataramani, Kaoutar El Maghraoui, Vijayalakshmi (Viji) Srinivasan, Kailash Gopalakrishnan
In this paper, we propose a number of novel techniques and numerical representation formats that enable, for the very first time, the precision of training systems to be aggressively scaled from 8-bits to 4-bits.
1 code implementation • ECCV 2020 • Ailing Zeng, Xiao Sun, Fuyang Huang, Minhao Liu, Qiang Xu, Stephen Lin
With the reduced dimensionality of less relevant body areas, the training set distribution within network branches more closely reflects the statistics of local poses instead of global body poses, without sacrificing information important for joint inference.
Ranked #7 on
Monocular 3D Human Pose Estimation
on Human3.6M
1 code implementation • 17 Jul 2020 • Dong-Jin Kim, Xiao Sun, Jinsoo Choi, Stephen Lin, In So Kweon
A common problem in human-object interaction (HOI) detection task is that numerous HOI classes have only a small number of labeled examples, resulting in training sets with a long-tailed distribution.
1 code implementation • ECCV 2020 • Fangyun Wei, Xiao Sun, Hongyang Li, Jingdong Wang, Stephen Lin
A recent approach for object detection and human pose estimation is to regress bounding boxes or human keypoints from a central point on the object or person.
no code implementations • NeurIPS 2019 • Xiao Sun, Jungwook Choi, Chia-Yu Chen, Naigang Wang, Swagath Venkataramani, Vijayalakshmi (Viji) Srinivasan, Xiaodong Cui, Wei zhang, Kailash Gopalakrishnan
Reducing the numerical precision of data and computation is extremely effective in accelerating deep learning training workloads.
no code implementations • 6 Nov 2019 • Xiao Sun, Zhouhui Lian, Jianguo Xiao
Point cloud analysis has drawn broader attentions due to its increasing demands in various fields.
no code implementations • 17 Apr 2019 • Jia Li, Xing Wei, Guoqiang Yang, Xiao Sun, Changliang Li
A multiscale shared convolution structure is adopted in the discriminator network to further supervise training the generator.
no code implementations • 17 Apr 2019 • Jia Li, Xiao Sun, Xing Wei, Changliang Li, Jian-Hua Tao
In recent years, the generation of conversation content based on deep neural networks has attracted many researchers.
no code implementations • 17 Nov 2018 • Xiao Sun, Chuankang Li, Stephen Lin
We present a method for human pose tracking that is based on learning spatiotemporal relationships among joints.
1 code implementation • 17 Sep 2018 • Xiao Sun, Chuankang Li, Stephen Lin
For the ECCV 2018 PoseTrack Challenge, we present a 3D human pose estimation system based mainly on the integral human pose regression method.
Ranked #1 on
3D Human Pose Estimation
on CHALL H80K
no code implementations • EMNLP 2018 • Jingyuan Li, Xiao Sun
Traditional neural language models tend to generate generic replies with poor logic and no emotion.
2 code implementations • ECCV 2018 • Xiao Sun, Bin Xiao, Fangyin Wei, Shuang Liang, Yichen Wei
State-of-the-art human pose estimation methods are based on heat map representation.
Ranked #19 on
Pose Estimation
on MPII Human Pose
5 code implementations • ICCV 2017 • Xingyi Zhou, Qi-Xing Huang, Xiao Sun, xiangyang xue, Yichen Wei
We propose a weakly-supervised transfer learning method that uses mixed 2D and 3D labels in a unified deep neutral network that presents two-stage cascaded structure.
1 code implementation • ICCV 2017 • Xiao Sun, Jiaxiang Shang, Shuang Liang, Yichen Wei
A central problem is that the structural information in the pose is not well exploited in the previous regression methods.
no code implementations • 17 Sep 2016 • Xingyi Zhou, Xiao Sun, Wei zhang, Shuang Liang, Yichen Wei
In this work, we propose to directly embed a kinematic object model into the deep neutral network learning for general articulated object pose estimation.
no code implementations • CVPR 2015 • Xiao Sun, Yichen Wei, Shuang Liang, Xiaoou Tang, Jian Sun
We extends the previous 2D cascaded object pose regression work [9] in two aspects so that it works better for 3D articulated objects.
no code implementations • CVPR 2014 • Chen Qian, Xiao Sun, Yichen Wei, Xiaoou Tang, Jian Sun
We present a realtime hand tracking system using a depth sensor.