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05/23/2023
Decoupled Kullback-Leibler Divergence Loss
In this paper, we delve deeper into the Kullback-Leibler (KL) Divergence...
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01/03/2023
Understanding Imbalanced Semantic Segmentation Through Neural Collapse
A recent study has shown a phenomenon called neural collapse in that the...
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09/26/2022
Generalized Parametric Contrastive Learning
In this paper, we propose the Generalized Parametric Contrastive Learnin...
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03/22/2022
Rebalanced Siamese Contrastive Mining for Long-Tailed Recognition
Deep neural networks perform poorly on heavily class-imbalanced datasets...
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07/26/2021
Parametric Contrastive Learning
In this paper, we propose Parametric Contrastive Learning (PaCo) to tack...
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04/01/2021
Improving Calibration for Long-Tailed Recognition
Deep neural networks may perform poorly when training datasets are heavi...
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01/26/2021
ResLT: Residual Learning for Long-tailed Recognition
Deep learning algorithms face great challenges with long-tailed data dis...
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07/31/2019
Expectation-Maximization Attention Networks for Semantic Segmentation
Self-attention mechanism has been widely used for various tasks. It is d...
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06/18/2019
ADA-Tucker: Compressing Deep Neural Networks via Adaptive Dimension Adjustment Tucker Decomposition
Despite the recent success of deep learning models in numerous applicati...
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05/15/2019
Differentiable Linearized ADMM
Recently, a number of learning-based optimization methods that combine d...
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09/12/2018
Joint Sub-bands Learning with Clique Structures for Wavelet Domain Super-Resolution
Convolutional neural networks (CNNs) have recently achieved great succes...
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02/28/2018
