Search Results for author: Qi She

Found 23 papers, 16 papers with code

MT-ORL: Multi-Task Occlusion Relationship Learning

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.

Unifying Nonlocal Blocks for Neural Networks

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.

Action Recognition Image Classification +2

Generative adversarial networks in time series: A survey and taxonomy

1 code implementation23 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.

Time Series

MINE: Towards Continuous Depth MPI with NeRF for Novel View Synthesis

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.

3D Reconstruction Depth Estimation +1

Learning the Superpixel in a Non-iterative and Lifelong Manner

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.

ACTION-Net: Multipath Excitation for Action Recognition

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.

Action Recognition

A Unified Framework to Analyze and Design the Nonlocal Blocks for Neural Networks

no code implementations1 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.

Action Recognition Fine-Grained Image Classification

CVPR 2020 Continual Learning in Computer Vision Competition: Approaches, Results, Current Challenges and Future Directions

1 code implementation14 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.

Continual Learning

CatNet: Class Incremental 3D ConvNets for Lifelong Egocentric Gesture Recognition

1 code implementation20 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.

Gesture Recognition Video Recognition

A Neuro-AI Interface for Evaluating Generative Adversarial Networks

1 code implementation5 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.

Speech Synthesis

OpenLORIS-Object: A Robotic Vision Dataset and Benchmark for Lifelong Deep Learning

2 code implementations15 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.

Object Recognition

A Spectral Nonlocal Block for Neural Networks

no code implementations4 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.

Action Recognition Fine-Grained Image Classification +2

Stochastic trajectory prediction with social graph network

no code implementations24 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.

Pedestrian Trajectory Prediction Trajectory Prediction

Neural Dynamics Discovery via Gaussian Process Recurrent Neural Networks

1 code implementation1 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.

Dimensionality Reduction Time Series +1

Generative Adversarial Networks in Computer Vision: A Survey and Taxonomy

3 code implementations4 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.

Image Inpainting Image Quality Assessment +3

Synthetic-Neuroscore: Using A Neuro-AI Interface for Evaluating Generative Adversarial Networks

1 code implementation10 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.

Image Generation Speech Synthesis

An Efficient and Flexible Spike Train Model via Empirical Bayes

no code implementations10 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.

Bayesian Inference

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