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07/01/2023
Filter Pruning for Efficient CNNs via Knowledge-driven Differential Filter Sampler
Filter pruning simultaneously accelerates the computation and reduces th...
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05/19/2023
AttriCLIP: A Non-Incremental Learner for Incremental Knowledge Learning
Continual learning aims to enable a model to incrementally learn knowled...
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12/15/2022
DCS-RISR: Dynamic Channel Splitting for Efficient Real-world Image Super-Resolution
Real-world image super-resolution (RISR) has received increased focus fo...
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06/02/2022
MISSU: 3D Medical Image Segmentation via Self-distilling TransUNet
U-Nets have achieved tremendous success in medical image segmentation. N...
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04/28/2022
A Closer Look at Branch Classifiers of Multi-exit Architectures
Multi-exit architectures consist of a backbone and branch classifiers th...
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06/18/2021
Novelty Detection via Contrastive Learning with Negative Data Augmentation
Novelty detection is the process of determining whether a query example ...
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05/25/2021
Towards Compact Single Image Super-Resolution via Contrastive Self-distillation
Convolutional neural networks (CNNs) are highly successful for super-res...
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05/24/2021
Towards Compact CNNs via Collaborative Compression
Channel pruning and tensor decomposition have received extensive attenti...
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04/19/2021
Contrastive Learning for Compact Single Image Dehazing
Single image dehazing is a challenging ill-posed problem due to the seve...
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04/07/2021
Farewell to Mutual Information: Variational Distillation for Cross-Modal Person Re-Identification
The Information Bottleneck (IB) provides an information theoretic princi...
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11/09/2020
PAMS: Quantized Super-Resolution via Parameterized Max Scale
Deep convolutional neural networks (DCNNs) have shown dominant performan...
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04/20/2020
Towards deep neural network compression via learnable wavelet transforms
Wavelets are well known for data compression, yet have rarely been appli...
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09/28/2019
Training convolutional neural networks with cheap convolutions and online distillation
The large memory and computation consumption in convolutional neural net...
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06/04/2019
Dynamic Neural Network Decoupling
Convolutional neural networks (CNNs) have achieved a superior performanc...
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03/22/2019
Towards Optimal Structured CNN Pruning via Generative Adversarial Learning
Structured pruning of filters or neurons has received increased focus fo...
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01/23/2019
Towards Compact ConvNets via Structure-Sparsity Regularized Filter Pruning
The success of convolutional neural networks (CNNs) in computer vision a...
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12/11/2018