1 code implementation • 7 Aug 2022 • Zhengyang Shen, Tao Hong, Qi She, Jinwen Ma, Zhouchen Lin
Steerable models can provide very general and flexible equivariance by formulating equivariance requirements in the language of representation theory and feature fields, which has been recognized to be effective for many vision tasks.
1 code implementation • CVPR 2022 • Lei Zhu, Qi She, Qian Chen, Yunfei You, Boyu Wang, Yanye Lu
To avoid this problem, this work provides a novel perspective that models WSOL as a domain adaption (DA) task, where the score estimator trained on the source/image domain is tested on the target/pixel domain to locate objects.
1 code implementation • CVPR 2022 • Li Yi, Sheng Liu, Qi She, A. Ian McLeod, Boyu Wang
To address this issue, we focus on learning robust contrastive representations of data on which the classifier is hard to memorize the label noise under the CE loss.
1 code implementation • 29 Dec 2021 • Lei Zhu, Qi She, Qian Chen, Xiangxi Meng, Mufeng Geng, Lujia Jin, Zhe Jiang, Bin Qiu, Yunfei You, Yibao Zhang, Qiushi Ren, Yanye Lu
In our B-CAM, two image-level features, aggregated by pixel-level features of potential background and object locations, are used to purify the object feature from the object-related background and to represent the feature of the pure-background sample, respectively.
1 code implementation • CVPR 2022 • Junfei Xiao, Longlong Jing, Lin Zhang, Ju He, Qi She, Zongwei Zhou, Alan Yuille, Yingwei Li
Our method achieves the state-of-the-art performance on three video action recognition benchmarks (i. e., Kinetics-400, UCF-101, and HMDB-51) under several typical semi-supervised settings (i. e., different ratios of labeled data).
1 code implementation • 17 Oct 2021 • Zhengwei Wang, Qi She, Aljosa Smolic
Video compression (e. g., H. 264, MPEG-4) reduces superfluous information by representing the raw video stream using the concept of Group of Pictures (GOP).
no code implementations • 6 Oct 2021 • Cheng Xu, Weimin WANG, Shuai Liu, Yong Wang, Yuxiang Tang, Tianling Bian, Yanyu Yan, Qi She, Cheng Yang
In this paper, we show our solution to the Google Landmark Recognition 2021 Competition.
1 code implementation • ICCV 2021 • Panhe Feng, Qi She, Lei Zhu, Jiaxin Li, Lin Zhang, Zijian Feng, Changhu Wang, Chunpeng Li, Xuejing Kang, Anlong Ming
Retrieving occlusion relation among objects in a single image is challenging due to sparsity of boundaries in image.
1 code implementation • ICCV 2021 • Lei Zhu, Qi She, Duo Li, Yanye Lu, Xuejing Kang, Jie Hu, Changhu Wang
The nonlocal-based blocks are designed for capturing long-range spatial-temporal dependencies in computer vision tasks.
1 code implementation • 23 Jul 2021 • Eoin Brophy, Zhengwei Wang, Qi She, Tomas Ward
We propose a taxonomy of discrete-variant GANs and continuous-variant GANs, in which GANs deal with discrete time series and continuous time series data.
1 code implementation • 2 Jul 2021 • Lin Zhang, Qi She, Zhengyang Shen, Changhu Wang
Contrastive learning applied to self-supervised representation learning has seen a resurgence in deep models.
4 code implementations • 1 Apr 2021 • Vincenzo Lomonaco, Lorenzo Pellegrini, Andrea Cossu, Antonio Carta, Gabriele Graffieti, Tyler L. Hayes, Matthias De Lange, Marc Masana, Jary Pomponi, Gido van de Ven, Martin Mundt, Qi She, Keiland Cooper, Jeremy Forest, Eden Belouadah, Simone Calderara, German I. Parisi, Fabio Cuzzolin, Andreas Tolias, Simone Scardapane, Luca Antiga, Subutai Amhad, Adrian Popescu, Christopher Kanan, Joost Van de Weijer, Tinne Tuytelaars, Davide Bacciu, Davide Maltoni
Learning continually from non-stationary data streams is a long-standing goal and a challenging problem in machine learning.
1 code implementation • ICCV 2021 • Jiaxin Li, Zijian Feng, Qi She, Henghui Ding, Changhu Wang, Gim Hee Lee
In this paper, we propose MINE to perform novel view synthesis and depth estimation via dense 3D reconstruction from a single image.
1 code implementation • CVPR 2021 • Lei Zhu, Qi She, Bin Zhang, Yanye Lu, Zhilin Lu, Duo Li, Jie Hu
Superpixel is generated by automatically clustering pixels in an image into hundreds of compact partitions, which is widely used to perceive the object contours for its excellent contour adherence.
1 code implementation • CVPR 2021 • Zhengwei Wang, Qi She, Aljosa Smolic
To this end, we propose a spAtio-temporal, Channel and moTion excitatION (ACTION) module consisting of three paths: Spatio-Temporal Excitation (STE) path, Channel Excitation (CE) path, and Motion Excitation (ME) path.
13 code implementations • CVPR 2021 • Duo Li, Jie Hu, Changhu Wang, Xiangtai Li, Qi She, Lei Zhu, Tong Zhang, Qifeng Chen
Convolution has been the core ingredient of modern neural networks, triggering the surge of deep learning in vision.
Ranked #706 on Image Classification on ImageNet
no code implementations • 1 Jan 2021 • Lei Zhu, Qi She, Changhu Wang
When choosing Chebyshev graph filter, a generalized formulation can be derived for explaining the existing nonlocal-based blocks (e. g. nonlocal block, nonlocal stage, double attention block) and uses to analyze their irrationality.
1 code implementation • 14 Sep 2020 • Vincenzo Lomonaco, Lorenzo Pellegrini, Pau Rodriguez, Massimo Caccia, Qi She, Yu Chen, Quentin Jodelet, Ruiping Wang, Zheda Mai, David Vazquez, German I. Parisi, Nikhil Churamani, Marc Pickett, Issam Laradji, Davide Maltoni
In the last few years, we have witnessed a renewed and fast-growing interest in continual learning with deep neural networks with the shared objective of making current AI systems more adaptive, efficient and autonomous.
no code implementations • 26 Apr 2020 • Qi She, Fan Feng, Qi Liu, Rosa H. M. Chan, Xinyue Hao, Chuanlin Lan, Qihan Yang, Vincenzo Lomonaco, German I. Parisi, Heechul Bae, Eoin Brophy, Baoquan Chen, Gabriele Graffieti, Vidit Goel, Hyonyoung Han, Sathursan Kanagarajah, Somesh Kumar, Siew-Kei Lam, Tin Lun Lam, Liang Ma, Davide Maltoni, Lorenzo Pellegrini, Duvindu Piyasena, ShiLiang Pu, Debdoot Sheet, Soonyong Song, Youngsung Son, Zhengwei Wang, Tomas E. Ward, Jianwen Wu, Meiqing Wu, Di Xie, Yangsheng Xu, Lin Yang, Qiaoyong Zhong, Liguang Zhou
This report summarizes IROS 2019-Lifelong Robotic Vision Competition (Lifelong Object Recognition Challenge) with methods and results from the top $8$ finalists (out of over~$150$ teams).
1 code implementation • 20 Apr 2020 • Zhengwei Wang, Qi She, Tejo Chalasani, Aljosa Smolic
Egocentric gestures are the most natural form of communication for humans to interact with wearable devices such as VR/AR helmets and glasses.
1 code implementation • 5 Mar 2020 • Zhengwei Wang, Qi She, Alan F. Smeaton, Tomas E. Ward, Graham Healy
In this work, we introduce an evaluation metric called Neuroscore, for evaluating the performance of GANs, that more directly reflects psychoperceptual image quality through the utilization of brain signals.
2 code implementations • 15 Nov 2019 • Qi She, Fan Feng, Xinyue Hao, Qihan Yang, Chuanlin Lan, Vincenzo Lomonaco, Xuesong Shi, Zhengwei Wang, Yao Guo, Yimin Zhang, Fei Qiao, Rosa H. M. Chan
Yet, robotic vision poses unique challenges for applying visual algorithms developed from these standard computer vision datasets due to their implicit assumption over non-varying distributions for a fixed set of tasks.
no code implementations • 13 Nov 2019 • Xuesong Shi, Dongjiang Li, Pengpeng Zhao, Qinbin Tian, Yuxin Tian, Qiwei Long, Chunhao Zhu, Jingwei Song, Fei Qiao, Le Song, Yangquan Guo, Zhigang Wang, Yimin Zhang, Baoxing Qin, Wei Yang, Fangshi Wang, Rosa H. M. Chan, Qi She
We also design benchmarking metrics for lifelong SLAM, with which the robustness and accuracy of pose estimation are evaluated separately.
no code implementations • 4 Nov 2019 • Lei Zhu, Qi She, Lidan Zhang, Ping Guo
The nonlocal-based blocks are designed for capturing long-range spatial-temporal dependencies in computer vision tasks.
no code implementations • 25 Sep 2019 • Lei Zhu, Qi She, Lidan Zhang, Ping Guo
The nonlocal network is designed for capturing long-range spatial-temporal dependencies in several computer vision tasks.
no code implementations • 24 Jul 2019 • Lidan Zhang, Qi She, Ping Guo
For the second issue, instead of modeling the uncertainty of the entire future as a whole, we utilize a temporal stochastic method for sequentially learning a prior model of uncertainty during social interactions.
1 code implementation • 1 Jul 2019 • Qi She, Anqi Wu
In the experiment, we show that our model outperforms other state-of-the-art methods in reconstructing insightful latent dynamics from both simulated and experimental neural datasets with either Gaussian or Poisson observations, especially in the low-sample scenario.
3 code implementations • 4 Jun 2019 • Zhengwei Wang, Qi She, Tomas E. Ward
While several reviews for GANs have been presented to date, none have considered the status of this field based on their progress towards addressing practical challenges relevant to computer vision.
no code implementations • 28 May 2019 • Zhengwei Wang, Qi She, Eoin Brophy, Alan F. Smeaton, Tomas E. Ward, Graham Healy
Deep neural networks (DNNs) are inspired from the human brain and the interconnection between the two has been widely studied in the literature.
1 code implementation • 10 May 2019 • Zhengwei Wang, Qi She, Alan F. Smeaton, Tomas E. Ward, Graham Healy
In this work, we describe an evaluation metric we call Neuroscore, for evaluating the performance of GANs, that more directly reflects psychoperceptual image quality through the utilization of brain signals.
no code implementations • 10 May 2016 • Qi She, Xiaoli Wu, Beth Jelfs, Adam S. Charles, Rosa H. M. Chan
Our method integrates both Generalized Linear Models (GLMs) and empirical Bayes theory, which aims to (1) improve the accuracy and reliability of parameter estimation, compared to the maximum likelihood-based method for NB-GLM and Poisson-GLM; (2) effectively capture the over-dispersion nature of spike counts from both simulated data and experimental data; and (3) provide insight into both neural interactions and spiking behaviours of the neuronal populations.