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07/14/2022
E2-AEN: End-to-End Incremental Learning with Adaptively Expandable Network
Expandable networks have demonstrated their advantages in dealing with c...
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01/13/2022
Technical Report for ICCV 2021 Challenge SSLAD-Track3B: Transformers Are Better Continual Learners
In the SSLAD-Track 3B challenge on continual learning, we propose the me...
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08/12/2021
m-RevNet: Deep Reversible Neural Networks with Momentum
In recent years, the connections between deep residual networks and firs...
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08/05/2021
Unifying Nonlocal Blocks for Neural Networks
The nonlocal-based blocks are designed for capturing long-range spatial-...
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04/05/2021
Potential Convolution: Embedding Point Clouds into Potential Fields
Recently, various convolutions based on continuous or discrete kernels f...
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03/19/2021
Learning the Superpixel in a Non-iterative and Lifelong Manner
Superpixel is generated by automatically clustering pixels in an image i...
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03/11/2021
PointFlow: Flowing Semantics Through Points for Aerial Image Segmentation
Aerial Image Segmentation is a particular semantic segmentation problem ...
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07/19/2020
Resolution Switchable Networks for Runtime Efficient Image Recognition
We propose a general method to train a single convolutional neural netwo...
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07/13/2020
PSConv: Squeezing Feature Pyramid into One Compact Poly-Scale Convolutional Layer
Despite their strong modeling capacities, Convolutional Neural Networks ...
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07/13/2020
Learning to Learn Parameterized Classification Networks for Scalable Input Images
Convolutional Neural Networks (CNNs) do not have a predictable recogniti...
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07/13/2020
Deep Reinforced Attention Learning for Quality-Aware Visual Recognition
In this paper, we build upon the weakly-supervised generation mechanism ...
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03/24/2020
Dynamic Hierarchical Mimicking Towards Consistent Optimization Objectives
While the depth of modern Convolutional Neural Networks (CNNs) surpasses...
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08/11/2019