no code implementations • ECCV 2020 • Wenyu Sun, Chen Tang, Weigui Li, Zhuqing Yuan, Huazhong Yang, Yongpan Liu
This paper proposes a deep video compression method to simultaneously encode multiple frames with Frame-Conv3D and differential modulation.
no code implementations • 8 Feb 2023 • Xinyi Yang, Shiyu Huang, Yiwen Sun, Yuxiang Yang, Chao Yu, Wei-Wei Tu, Huazhong Yang, Yu Wang
Goal-conditioned hierarchical reinforcement learning (HRL) provides a promising direction to tackle this challenge by introducing a hierarchical structure to decompose the search space, where the low-level policy predicts primitive actions in the guidance of the goals derived from the high-level policy.
Hierarchical Reinforcement Learning Multi-agent Reinforcement Learning +2
no code implementations • 9 Jan 2023 • Chao Yu, Xinyi Yang, Jiaxuan Gao, Jiayu Chen, Yunfei Li, Jijia Liu, Yunfei Xiang, Ruixin Huang, Huazhong Yang, Yi Wu, Yu Wang
Simply waiting for every robot being ready for the next action can be particularly time-inefficient.
Multi-agent Reinforcement Learning reinforcement-learning +1
no code implementations • 23 Nov 2022 • Guodong Yin, Mufeng Zhou, Yiming Chen, Wenjun Tang, Zekun Yang, Mingyen Lee, Xirui Du, Jinshan Yue, Jiaxin Liu, Huazhong Yang, Yongpan Liu, Xueqing Li
Performing data-intensive tasks in the von Neumann architecture is challenging to achieve both high performance and power efficiency due to the memory wall bottleneck.
no code implementations • 31 Oct 2022 • Ruoyang Liu, Chenhan Wei, Yixiong Yang, Wenxun Wang, Huazhong Yang, Yongpan Liu
Data quantization is an effective method to accelerate neural network training and reduce power consumption.
no code implementations • 17 Oct 2022 • Ranran Huang, Yu Wang, Huazhong Yang
Learning discriminative representations for subtle localized details plays a significant role in Fine-grained Visual Categorization (FGVC).
1 code implementation • 16 Jul 2022 • Zixuan Zhou, Xuefei Ning, Yi Cai, Jiashu Han, Yiping Deng, Yuhan Dong, Huazhong Yang, Yu Wang
Specifically, we train the supernet with a large sharing extent (an easier curriculum) at the beginning and gradually decrease the sharing extent of the supernet (a harder curriculum).
no code implementations • 12 Dec 2021 • Weilin Liu, Ye Mu, Chao Yu, Xuefei Ning, Zhong Cao, Yi Wu, Shuang Liang, Huazhong Yang, Yu Wang
These scenarios indeed correspond to the vulnerabilities of the under-test driving policies, thus are meaningful for their further improvements.
1 code implementation • NeurIPS 2021 • Jiayu Chen, Yuanxin Zhang, Yuanfan Xu, Huimin Ma, Huazhong Yang, Jiaming Song, Yu Wang, Yi Wu
We motivate our paradigm through a variational perspective, where the learning objective can be decomposed into two terms: task learning on the current task distribution, and curriculum update to a new task distribution.
no code implementations • 12 Oct 2021 • Chao Yu, Xinyi Yang, Jiaxuan Gao, Huazhong Yang, Yu Wang, Yi Wu
In this paper, we extend the state-of-the-art single-agent visual navigation method, Active Neural SLAM (ANS), to the multi-agent setting by introducing a novel RL-based planning module, Multi-agent Spatial Planner (MSP). MSP leverages a transformer-based architecture, Spatial-TeamFormer, which effectively captures spatial relations and intra-agent interactions via hierarchical spatial self-attentions.
no code implementations • AAAI Workshop AdvML 2022 • Yi Cai, Xuefei Ning, Huazhong Yang, Yu Wang
It provides high scalability because the paths within an EIO network exponentially increase with the network depth.
no code implementations • 2 Feb 2021 • Guodong Yin, Yi Cai, Juejian Wu, Zhengyang Duan, Zhenhua Zhu, Yongpan Liu, Yu Wang, Huazhong Yang, Xueqing Li
Compute-in-memory (CiM) is a promising approach to alleviating the memory wall problem for domain-specific applications.
1 code implementation • 10 Jan 2021 • Guyue Huang, Jingbo Hu, Yifan He, Jialong Liu, Mingyuan Ma, Zhaoyang Shen, Juejian Wu, Yuanfan Xu, Hengrui Zhang, Kai Zhong, Xuefei Ning, Yuzhe ma, HaoYu Yang, Bei Yu, Huazhong Yang, Yu Wang
With the down-scaling of CMOS technology, the design complexity of very large-scale integrated (VLSI) is increasing.
no code implementations • 1 Jan 2021 • Kai Zhong, Xuefei Ning, Tianchen Zhao, Zhenhua Zhu, Shulin Zeng, Guohao Dai, Yu Wang, Huazhong Yang
Through this dynamic precision framework, we can reduce the bit-width of convolution, which is the most computational cost, while keeping the training process close to the full precision floating-point training.
1 code implementation • 22 Dec 2020 • Xuefei Ning, Junbo Zhao, Wenshuo Li, Tianchen Zhao, Yin Zheng, Huazhong Yang, Yu Wang
In this paper, considering scenarios with capacity budget, we aim to discover adversarially robust architecture at targeted capacities.
1 code implementation • 25 Nov 2020 • Xuefei Ning, Changcheng Tang, Wenshuo Li, Songyi Yang, Tianchen Zhao, Niansong Zhang, Tianyi Lu, Shuang Liang, Huazhong Yang, Yu Wang
Neural Architecture Search (NAS) has received extensive attention due to its capability to discover neural network architectures in an automated manner.
no code implementations • 21 Nov 2020 • Tianchen Zhao, Xuefei Ning, Xiangsheng Shi, Songyi Yang, Shuang Liang, Peng Lei, Jianfei Chen, Huazhong Yang, Yu Wang
We also design the micro-level search space to strengthen the information flow for BNN.
no code implementations • 18 Nov 2020 • Feng Gao, Jincheng Yu, Hao Shen, Yu Wang, Huazhong Yang
Learning depth and ego-motion from unlabeled videos via self-supervision from epipolar projection can improve the robustness and accuracy of the 3D perception and localization of vision-based robots.
no code implementations • 28 Sep 2020 • Xuefei Ning, Wenshuo Li, Zixuan Zhou, Tianchen Zhao, Shuang Liang, Yin Zheng, Huazhong Yang, Yu Wang
A major challenge in NAS is to conduct a fast and accurate evaluation of neural architectures.
1 code implementation • NeurIPS 2021 • Xuefei Ning, Changcheng Tang, Wenshuo Li, Zixuan Zhou, Shuang Liang, Huazhong Yang, Yu Wang
Conducting efficient performance estimations of neural architectures is a major challenge in neural architecture search (NAS).
no code implementations • 31 Jul 2020 • Tong Wu, Xuefei Ning, Wenshuo Li, Ranran Huang, Huazhong Yang, Yu Wang
In this paper, we tackle the issue of physical adversarial examples for object detectors in the wild.
2 code implementations • 7 Jul 2020 • Guyue Huang, Guohao Dai, Yu Wang, Huazhong Yang
GE-SpMM performs SpMM-like operation on sparse matrices represented in the most common Compressed Sparse Row (CSR) format, so it can be embedded in GNN frameworks with no preprocessing overheads and support general GNN algorithms.
Distributed, Parallel, and Cluster Computing
no code implementations • 4 Jun 2020 • Kai Zhong, Xuefei Ning, Guohao Dai, Zhenhua Zhu, Tianchen Zhao, Shulin Zeng, Yu Wang, Huazhong Yang
For training a variety of models on CIFAR-10, using 1-bit mantissa and 2-bit exponent is adequate to keep the accuracy loss within $1\%$.
1 code implementation • ECCV 2020 • Xuefei Ning, Tianchen Zhao, Wenshuo Li, Peng Lei, Yu Wang, Huazhong Yang
In budgeted pruning, how to distribute the resources across layers (i. e., sparsity allocation) is the key problem.
1 code implementation • ECCV 2020 • Xuefei Ning, Yin Zheng, Tianchen Zhao, Yu Wang, Huazhong Yang
Experimental results on various search spaces confirm GATES's effectiveness in improving the performance predictor.
no code implementations • 26 Mar 2020 • Shulin Zeng, Guohao Dai, Hanbo Sun, Kai Zhong, Guangjun Ge, Kaiyuan Guo, Yu Wang, Huazhong Yang
Currently, the majority of FPGA-based DNN accelerators in the cloud run in a time-division multiplexing way for multiple users sharing a single FPGA, and require re-compilation with $\sim$100 s overhead.
no code implementations • 20 Mar 2020 • Xuefei Ning, Guangjun Ge, Wenshuo Li, Zhenhua Zhu, Yin Zheng, Xiaoming Chen, Zhen Gao, Yu Wang, Huazhong Yang
By inspecting the discovered architectures, we find that the operation primitives, the weight quantization range, the capacity of the model, and the connection pattern have influences on the fault resilience capability of NN models.
no code implementations • 18 Jun 2018 • Xuefei Ning, Yin Zheng, Zhuxi Jiang, Yu Wang, Huazhong Yang, Junzhou Huang
Moreover, we also propose HiTM-VAE, where the document-specific topic distributions are generated in a hierarchical manner.
no code implementations • 14 May 2018 • Wenshuo Li, Jincheng Yu, Xuefei Ning, Pengjun Wang, Qi Wei, Yu Wang, Huazhong Yang
So, in this paper, we propose a hardware-software collaborative attack framework to inject hidden neural network Trojans, which works as a back-door without requiring manipulating input images and is flexible for different scenarios.
no code implementations • 26 Apr 2018 • Yi Wei, Guijin Wang, Cairong Zhang, Hengkai Guo, Xinghao Chen, Huazhong Yang
Different from previous works, we propose a new framework, named Two-Stream Binocular Network (TSBnet) to detect fingertips from binocular images directly.
no code implementations • 2 Apr 2018 • Cairong Zhang, Guijin Wang, Hengkai Guo, Xinghao Chen, Fei Qiao, Huazhong Yang
In the reality of HMI, joints in fingers stretching out, especially corresponding fingertips, are much more important than other joints.
no code implementations • ICLR 2018 • Xuefei Ning, Yin Zheng, Zhuxi Jiang, Yu Wang, Huazhong Yang, Junzhou Huang
On the other hand, different with the other BNP topic models, the inference of iTM-VAE is modeled by neural networks, which has rich representation capacity and can be computed in a simple feed-forward manner.
no code implementations • 24 Dec 2017 • Kaiyuan Guo, Shulin Zeng, Jincheng Yu, Yu Wang, Huazhong Yang
Various FPGA based accelerator designs have been proposed with software and hardware optimization techniques to achieve high speed and energy efficiency.
no code implementations • 16 Jun 2017 • Yuzhi Wang, Anqi Yang, Xiaoming Chen, Pengjun Wang, Yu Wang, Huazhong Yang
Temporal drift of sensory data is a severe problem impacting the data quality of wireless sensor networks (WSNs).
no code implementations • 8 Feb 2017 • Hengkai Guo, Guijin Wang, Xinghao Chen, Cairong Zhang, Fei Qiao, Huazhong Yang
Hand pose estimation from monocular depth images is an important and challenging problem for human-computer interaction.
Ranked #10 on Hand Pose Estimation on MSRA Hands
no code implementations • 1 Dec 2016 • Song Han, Junlong Kang, Huizi Mao, Yiming Hu, Xin Li, Yubin Li, Dongliang Xie, Hong Luo, Song Yao, Yu Wang, Huazhong Yang, William J. Dally
Evaluated on the LSTM for speech recognition benchmark, ESE is 43x and 3x faster than Core i7 5930k CPU and Pascal Titan X GPU implementations.
no code implementations • 11 Aug 2014 • Yi Li, Qi Wei, Fei Qiao, Huazhong Yang
In this paper, we propose an active circuit network to implement multi-scale Gaussian filter, which is also called Gaussian Pyramid in image preprocessing.