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06/29/2023
Understanding the Overfitting of the Episodic Meta-training
Despite the success of two-stage few-shot classification methods, in the...
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05/12/2023
T-former: An Efficient Transformer for Image Inpainting
Benefiting from powerful convolutional neural networks (CNNs), learning-...
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04/25/2023
Pseudo Labels Refinement with Intra-camera Similarity for Unsupervised Person Re-identification
Unsupervised person re-identification (Re-ID) aims to retrieve person im...
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11/14/2021
Auxiliary Loss Adaption for Image Inpainting
Auxiliary losses commonly used in image inpainting lead to better recons...
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12/12/2020
Teacher-Student Asynchronous Learning with Multi-Source Consistency for Facial Landmark Detection
Due to the high annotation cost of large-scale facial landmark detection...
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07/13/2020
End-to-End Multi-Object Tracking with Global Response Map
Most existing Multi-Object Tracking (MOT) approaches follow the Tracking...
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07/07/2020
Meta Corrupted Pixels Mining for Medical Image Segmentation
Deep neural networks have achieved satisfactory performance in piles of ...
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03/18/2020
STH: Spatio-Temporal Hybrid Convolution for Efficient Action Recognition
Effective and Efficient spatio-temporal modeling is essential for action...
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01/30/2020
Multiple Object Tracking by Flowing and Fusing
Most of Multiple Object Tracking (MOT) approaches compute individual tar...
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11/29/2019
Collaborative Attention Network for Person Re-identification
Jointly utilizing global and local features to improve model accuracy is...
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11/19/2019
Distributed Generative Adversarial Net
Recently the Generative Adversarial Network has become a hot topic. Cons...
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09/16/2019
Particle reconstruction of volumetric particle image velocimetry with strategy of machine learning
Three-dimensional particle reconstruction with limited two-dimensional p...
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05/06/2019
Frame-wise Motion and Appearance for Real-time Multiple Object Tracking
The main challenge of Multiple Object Tracking (MOT) is the efficiency i...
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03/29/2019
SE2Net: Siamese Edge-Enhancement Network for Salient Object Detection
Deep convolutional neural network significantly boosted the capability o...
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09/08/2018
Video Smoke Detection Based on Deep Saliency Network
Video smoke detection is a promising fire detection method especially in...
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07/04/2018
Discriminative Feature Learning with Foreground Attention for Person Re-Identification
The performance of person re-identification (Re-ID) seriously depends on...
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10/07/2017
Deep Self-Paced Learning for Person Re-Identification
Person re-identification (Re-ID) usually suffers from noisy samples with...
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10/05/2017
Tracking Persons-of-Interest via Unsupervised Representation Adaptation
Multi-face tracking in unconstrained videos is a challenging problem as ...
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09/24/2017
Domain Adaptation from Synthesis to Reality in Single-model Detector for Video Smoke Detection
This paper proposes a method for video smoke detection using synthetic s...
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08/18/2017
Large Margin Learning in Set to Set Similarity Comparison for Person Re-identification
Person re-identification (Re-ID) aims at matching images of the same per...
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07/03/2017
Deep Ranking Model by Large Adaptive Margin Learning for Person Re-identification
Person re-identification aims to match images of the same person across ...
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03/31/2017
Single Image Super Resolution - When Model Adaptation Matters
In the recent years impressive advances were made for single image super...
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03/31/2017
Deep Domain Adaptation Based Video Smoke Detection using Synthetic Smoke Images
In this paper, a deep domain adaptation based method for video smoke det...
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03/23/2017
