no code implementations • 1 Feb 2024 • Qi Feng, Xinzhe Zuo, Wuchen Li
We also verify the convergence condition for the underdamped Langevin dynamics.
no code implementations • 20 Jan 2024 • Shengyao Chen, Qi Feng, Longyao Ran, Feng Xi, Zhong Liu
To maximize the output signal-to-interference-plus-noise ratio (SINR) of receive array, we formulate the codesign of transmit beamforming and RIS-assisted receive beamforming into a nonconvex constrained fractional programming problem, and then propose an alternating minimization-based algorithm to jointly optimize the transmitor beamfmer, receive beamformer and RIS reflection coefficients.
no code implementations • 6 Jan 2024 • Wei Deng, Yu Chen, Nicole Tianjiao Yang, Hengrong Du, Qi Feng, Ricky T. Q. Chen
Diffusion models have become the go-to method for large-scale generative models in real-world applications.
no code implementations • 30 Sep 2023 • Taichi Higasa, Keitaro Tanaka, Qi Feng, Shigeo Morishima
Language learners should regularly engage in reading challenging materials as part of their study routine.
no code implementations • 19 Sep 2023 • Ryosuke Oshima, Seitaro Shinagawa, Hideki Tsunashima, Qi Feng, Shigeo Morishima
Effective communication between humans and intelligent agents has promising applications for solving complex problems.
no code implementations • 24 Aug 2023 • Qi Feng, Hubert P. H. Shum, Shigeo Morishima
To explore this influence, we first propose a pilot study that captures real environments with multiple eye heights and asks participants to judge the egocentric distances and immersion.
no code implementations • 23 May 2023 • Sara Kashiwagi, Keitaro Tanaka, Qi Feng, Shigeo Morishima
This paper presents a novel metric learning approach to address the performance gap between normal and silent speech in visual speech recognition (VSR).
no code implementations • 15 Apr 2023 • Milind Naphade, Shuo Wang, David C. Anastasiu, Zheng Tang, Ming-Ching Chang, Yue Yao, Liang Zheng, Mohammed Shaiqur Rahman, Meenakshi S. Arya, Anuj Sharma, Qi Feng, Vitaly Ablavsky, Stan Sclaroff, Pranamesh Chakraborty, Sanjita Prajapati, Alice Li, Shangru Li, Krishna Kunadharaju, Shenxin Jiang, Rama Chellappa
The AI City Challenge's seventh edition emphasizes two domains at the intersection of computer vision and artificial intelligence - retail business and Intelligent Traffic Systems (ITS) - that have considerable untapped potential.
1 code implementation • 21 Nov 2022 • Erhan Bayraktar, Qi Feng, Zhaoyu Zhang
We extend the backward scheme in [Hur\'e-Pham-Warin.
no code implementations • 20 Nov 2022 • Wei Deng, Qian Zhang, Qi Feng, Faming Liang, Guang Lin
Notably, in big data scenarios, we obtain an appealing communication cost $O(P\log P)$ based on the optimal window size.
1 code implementation • ICCV 2023 • Tongkun Guan, Wei Shen, Xue Yang, Qi Feng, Zekun Jiang, Xiaokang Yang
Therefore, exploring the robust text feature representations on unlabeled real images by self-supervised learning is a good solution.
1 code implementation • Pattern Recognition and Computer Vision 2022 • Le Zhang, Qi Feng, Yao Lu, Chang Liu, and Guangming Lu
Attention mechanisms can effectively improve the performance of the mobile networks with a limited computational complexity cost.
1 code implementation • 21 Jul 2022 • Liangqi Zhang, Haibo Shen, Yihao Luo, Xiang Cao, Leixilan Pan, Tianjiang Wang, Qi Feng
Our VGNetG-1. 0MP achieves 67. 7% top-1 accuracy with 0. 99M parameters and 69. 2% top-1 accuracy with 1. 14M parameters on ImageNet classification dataset.
2 code implementations • 21 Apr 2022 • Milind Naphade, Shuo Wang, David C. Anastasiu, Zheng Tang, Ming-Ching Chang, Yue Yao, Liang Zheng, Mohammed Shaiqur Rahman, Archana Venkatachalapathy, Anuj Sharma, Qi Feng, Vitaly Ablavsky, Stan Sclaroff, Pranamesh Chakraborty, Alice Li, Shangru Li, Rama Chellappa
The four challenge tracks of the 2022 AI City Challenge received participation requests from 254 teams across 27 countries.
1 code implementation • CVPR 2023 • Tongkun Guan, Chaochen Gu, Jingzheng Tu, Xue Yang, Qi Feng, Yudi Zhao, Xiaokang Yang, Wei Shen
Supervised attention can alleviate the above issue, but it is character category-specific, which requires extra laborious character-level bounding box annotations and would be memory-intensive when handling languages with larger character categories.
Ranked #2 on Scene Text Recognition on ICDAR 2003
1 code implementation • 16 Feb 2022 • Qi Feng, Hubert P. H. Shum, Shigeo Morishima
In this work, we first establish a large-scale dataset with varied settings called Depth360 to tackle the training data problem.
1 code implementation • 27 Dec 2021 • Qi Feng, Kun He, He Wen, Cem Keskin, Yuting Ye
Notably, on CMU Panoptic Studio, we are able to reduce the turn-around time by 60% and annotation cost by 80% when compared to the conventional annotation process.
1 code implementation • 25 Oct 2021 • Tongkun Guan, Chaochen Gu, Changsheng Lu, Jingzheng Tu, Qi Feng, Kaijie Wu, Xinping Guan
Then, an attentive refinement network is developed by the attention map to rectify the location deviation of candidate boxes.
1 code implementation • 18 Oct 2021 • Fuqin Deng, Hua Feng, Mingjian Liang, Qi Feng, Ningbo Yi, Yong Yang, Yuan Gao, Junfeng Chen, Tin Lun Lam
The occupancy grid map is a critical component of autonomous positioning and navigation in the mobile robotic system, as many other systems' performance depends heavily on it.
no code implementations • 29 Sep 2021 • Wei Deng, Qian Zhang, Qi Feng, Faming Liang, Guang Lin
Parallel tempering (PT), also known as replica exchange, is the go-to workhorse for simulations of multi-modal distributions.
no code implementations • 24 Aug 2021 • Qi Feng, Man Luo, Zhaoyu Zhang
We propose a deep signature/log-signature FBSDE algorithm to solve forward-backward stochastic differential equations (FBSDEs) with state and path dependent features.
no code implementations • 9 Aug 2021 • Yihao Luo, Xiang Cao, Juntao Zhang, Peng Cheng, Tianjiang Wang, Qi Feng
With the continuous improvement of the performance of object detectors via advanced model architectures, imbalance problems in the training process have received more attention.
1 code implementation • 25 Apr 2021 • Milind Naphade, Shuo Wang, David C. Anastasiu, Zheng Tang, Ming-Ching Chang, Xiaodong Yang, Yue Yao, Liang Zheng, Pranamesh Chakraborty, Christian E. Lopez, Anuj Sharma, Qi Feng, Vitaly Ablavsky, Stan Sclaroff
Track 3 addressed city-scale multi-target multi-camera vehicle tracking.
1 code implementation • 19 Mar 2021 • Yihao Luo, Juntao Zhang, Xiang Cao, Jingjuan Guo, Haibo Shen, Tianjiang Wang, Qi Feng
Instead of the original 1x1 convolution and linear upsampling, it mitigates the information loss due to channel reduction.
1 code implementation • 12 Jan 2021 • Qi Feng, Vitaly Ablavsky, Stan Sclaroff
In this paper, we focus on two foundational tasks: the Vehicle Retrieval by NL task and the Vehicle Tracking by NL task, which take advantage of the proposed CityFlow-NL benchmark and provide a strong basis for future research on the multi-target multi-camera tracking by NL description task.
no code implementations • 7 Jan 2021 • Bhaskar Krishnamachari, Qi Feng, Eugenio Grippo
In particular, dramatic market price changes can result in low liquidity with respect to one or more of the assets and reduce the total value of the LP.
no code implementations • 16 Nov 2020 • Qi Feng, Wuchen Li
We formulate explicit bounds to guarantee the exponential dissipation for some non-gradient stochastic differential equations towards their invariant distributions.
Probability Dynamical Systems Optimization and Control
1 code implementation • ICLR 2021 • Wei Deng, Qi Feng, Georgios Karagiannis, Guang Lin, Faming Liang
Replica exchange stochastic gradient Langevin dynamics (reSGLD) has shown promise in accelerating the convergence in non-convex learning; however, an excessively large correction for avoiding biases from noisy energy estimators has limited the potential of the acceleration.
2 code implementations • ICML 2020 • Wei Deng, Qi Feng, Liyao Gao, Faming Liang, Guang Lin
Replica exchange Monte Carlo (reMC), also known as parallel tempering, is an important technique for accelerating the convergence of the conventional Markov Chain Monte Carlo (MCMC) algorithms.
Ranked #77 on Image Classification on CIFAR-100 (using extra training data)
no code implementations • 17 Mar 2020 • Yihao Luo, Min Xu, Caihong Yuan, Xiang Cao, Liangqi Zhang, Yan Xu, Tianjiang Wang, Qi Feng
Recently spiking neural networks (SNNs), the third-generation of neural networks has shown remarkable capabilities of energy-efficient computing, which is a promising alternative for deep neural networks (DNNs) with high energy consumption.
1 code implementation • CVPR 2021 • Qi Feng, Vitaly Ablavsky, Qinxun Bai, Stan Sclaroff
We propose a novel Siamese Natural Language Tracker (SNLT), which brings the advancements in visual tracking to the tracking by natural language (NL) descriptions task.
1 code implementation • ECCV 2020 • Chenhongyi Yang, Vitaly Ablavsky, Kaihong Wang, Qi Feng, Margrit Betke
While visual object detection with deep learning has received much attention in the past decade, cases when heavy intra-class occlusions occur have not been studied thoroughly.
no code implementations • 26 Jul 2019 • Qi Feng, Vitaly Ablavsky, Qinxun Bai, Guorong Li, Stan Sclaroff
In benchmarks, our method is competitive with state of the art trackers, while it outperforms all other trackers on targets with unambiguous and precise language annotations.