b'Guo-Jun Qi'

research

∙ 05/06/2022

Multitask AET with Orthogonal Tangent Regularity for Dark Object Detection

Dark environment becomes a challenge for computer vision algorithms owin...

Ziteng Cui, et al. ∙

research

∙ 04/19/2022

CTCNet: A CNN-Transformer Cooperation Network for Face Image Super-Resolution

Recently, deep convolution neural networks (CNNs) steered face super-res...

Guangwei Gao, et al. ∙

research

∙ 03/27/2022

CaCo: Both Positive and Negative Samples are Directly Learnable via Cooperative-adversarial Contrastive Learning

As a representative self-supervised method, contrastive learning has ach...

Xiao Wang, et al. ∙

research

∙ 01/22/2022

Dual-Flattening Transformers through Decomposed Row and Column Queries for Semantic Segmentation

It is critical to obtain high resolution features with long range depend...

Ying Wang, et al. ∙

research

∙ 01/07/2022

RestoreDet: Degradation Equivariant Representation for Object Detection in Low Resolution Images

Image restoration algorithms such as super resolution (SR) are indispens...

Ziteng Cui, et al. ∙

research

∙ 04/15/2021

Contrastive Learning with Stronger Augmentations

Representation learning has significantly been developed with the advanc...

Xiao Wang, et al. ∙

research

∙ 03/25/2021

Hierarchical Deep CNN Feature Set-Based Representation Learning for Robust Cross-Resolution Face Recognition

Cross-resolution face recognition (CRFR), which is important in intellig...

Guangwei Gao, et al. ∙

research

∙ 10/08/2020

Improved Techniques for Model Inversion Attacks

Model inversion (MI) attacks in the whitebox setting are aimed at recons...

Si Chen, et al. ∙

research

∙ 07/27/2020

K-Shot Contrastive Learning of Visual Features with Multiple Instance Augmentations

In this paper, we propose the K-Shot Contrastive Learning (KSCL) of visu...

Haohang Xu, et al. ∙

research

∙ 05/09/2020

Human in Events: A Large-Scale Benchmark for Human-centric Video Analysis in Complex Events

Along with the development of the modern smart city, human-centric video...

Weiyao Lin, et al. ∙

research

∙ 01/09/2020

Spatial-Temporal Transformer Networks for Traffic Flow Forecasting

Traffic forecasting has emerged as a core component of intelligent trans...

Mingxing Xu, et al. ∙

research

∙ 11/21/2019

EnAET: Self-Trained Ensemble AutoEncoding Transformations for Semi-Supervised Learning

Deep neural networks have been successfully applied to many real-world a...

Xiao Wang, et al. ∙

research

∙ 11/19/2019

GraphTER: Unsupervised Learning of Graph Transformation Equivariant Representations via Auto-Encoding Node-wise Transformations

Recent advances in Graph Convolutional Neural Networks (GCNNs) have show...

Xiang Gao, et al. ∙

research

∙ 11/16/2019

AETv2: AutoEncoding Transformations for Self-Supervised Representation Learning by Minimizing Geodesic Distances in Lie Groups

Self-supervised learning by predicting transformations has demonstrated ...

Feng Lin, et al. ∙

research

∙ 10/25/2019

Progressive Unsupervised Person Re-identification by Tracklet Association with Spatio-Temporal Regularization

Existing methods for person re-identification (Re-ID) are mostly based o...

Qiaokang Xie, et al. ∙

research

∙ 09/29/2019

Spatiotemporal Co-attention Recurrent Neural Networks for Human-Skeleton Motion Prediction

Human motion prediction aims to generate future motions based on the obs...

Xiangbo Shu, et al. ∙

research

∙ 07/12/2019

PC-DARTS: Partial Channel Connections for Memory-Efficient Differentiable Architecture Search

Differentiable architecture search (DARTS) provided a fast solution in f...

Yuhui Xu, et al. ∙

research

∙ 06/19/2019

Learning Generalized Transformation Equivariant Representations via Autoencoding Transformations

Learning Transformation Equivariant Representations (TERs) seeks to capt...

Guo-Jun Qi, et al. ∙

research

∙ 05/09/2019

Differential Recurrent Neural Network and its Application for Human Activity Recognition

The Long Short-Term Memory (LSTM) recurrent neural network is capable of...

Naifan Zhuang, et al. ∙

research

∙ 03/27/2019

Small Data Challenges in Big Data Era: A Survey of Recent Progress on Unsupervised and Semi-Supervised Methods

Small data challenges have emerged in many learning problems, since the ...

Guo-Jun Qi, et al. ∙

research

∙ 03/23/2019

AVT: Unsupervised Learning of Transformation Equivariant Representations by Autoencoding Variational Transformations

The learning of Transformation-Equivariant Representations (TERs), which...

Guo-Jun Qi, et al. ∙

research

∙ 02/15/2019

Learning to Adaptively Scale Recurrent Neural Networks

Recent advancements in recurrent neural network (RNN) research have demo...

Hao Hu, et al. ∙

research

∙ 01/14/2019

AET vs. AED: Unsupervised Representation Learning by Auto-Encoding Transformations rather than Data

The success of deep neural networks often relies on a large amount of la...

Liheng Zhang, et al. ∙

research

∙ 01/09/2019

Deep Semantic Multimodal Hashing Network for Scalable Multimedia Retrieval

Hashing has been widely applied to multimodal retrieval on large-scale m...

Lu Jin, et al. ∙

research

∙ 11/01/2018

Hierarchical Long Short-Term Concurrent Memory for Human Interaction Recognition

In this paper, we aim to address the problem of human interaction recogn...

Xiangbo Shu, et al. ∙

research

∙ 05/25/2018

A Study of Question Effectiveness Using Reddit "Ask Me Anything" Threads

Asking effective questions is a powerful social skill. In this paper we ...

Kristjan Arumae, et al. ∙

research

∙ 05/20/2018

Task-Agnostic Meta-Learning for Few-shot Learning

Meta-learning approaches have been proposed to tackle the few-shot learn...

Muhammad Abdullah Jamal, et al. ∙

research

∙ 05/19/2018

CapProNet: Deep Feature Learning via Orthogonal Projections onto Capsule Subspaces

In this paper, we formalize the idea behind capsule nets of using a caps...

Liheng Zhang, et al. ∙

research

∙ 05/07/2018

Deep Ordinal Hashing with Spatial Attention

Hashing has attracted increasing research attentions in recent years due...

Lu Jin, et al. ∙

research

∙ 05/07/2018

Sharp Attention Network via Adaptive Sampling for Person Re-identification

In this paper, we present novel sharp attention networks by adaptively s...

Chen Shen, et al. ∙

research

∙ 04/17/2018

IGCV2: Interleaved Structured Sparse Convolutional Neural Networks

In this paper, we study the problem of designing efficient convolutional...

Guotian Xie, et al. ∙

research

∙ 04/11/2018

Deep Differential Recurrent Neural Networks

Due to the special gating schemes of Long Short-Term Memory (LSTM), LSTM...

Naifan Zhuang, et al. ∙

research

∙ 11/16/2017

Global versus Localized Generative Adversarial Nets

In this paper, we present a novel localized Generative Adversarial Net (...

Guo-Jun Qi, et al. ∙

research

∙ 07/10/2017

Interleaved Group Convolutions for Deep Neural Networks

In this paper, we present a simple and modularized neural network archit...

Ting Zhang, et al. ∙

research

∙ 06/03/2017

Concurrence-Aware Long Short-Term Sub-Memories for Person-Person Action Recognition

Recently, Long Short-Term Memory (LSTM) has become a popular choice to m...

Xiangbo Shu, et al. ∙

research

∙ 03/22/2017

Joint Intermodal and Intramodal Label Transfers for Extremely Rare or Unseen Classes

In this paper, we present a label transfer model from texts to images fo...

Guo-Jun Qi, et al. ∙

research

∙ 01/23/2017

Loss-Sensitive Generative Adversarial Networks on Lipschitz Densities

*New Theory Result* We analyze the generalizability of the LS-GAN, showi...

Guo-Jun Qi, et al. ∙

research

∙ 06/06/2015

First-Take-All: Temporal Order-Preserving Hashing for 3D Action Videos

With the prevalence of the commodity depth cameras, the new paradigm of ...

Jun Ye, et al. ∙

research

∙ 04/25/2015

Differential Recurrent Neural Networks for Action Recognition

The long short-term memory (LSTM) neural network is capable of processin...

Vivek Veeriah, et al. ∙

Guo-Jun Qi

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