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06/13/2022
Singular Value Fine-tuning: Few-shot Segmentation requires Few-parameters Fine-tuning
Freezing the pre-trained backbone has become a standard paradigm to avoi...
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04/04/2022
Soft Threshold Ternary Networks
Large neural networks are difficult to deploy on mobile devices because ...
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01/25/2022
Revisiting L1 Loss in Super-Resolution: A Probabilistic View and Beyond
Super-resolution as an ill-posed problem has many high-resolution candid...
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12/28/2021
APRIL: Finding the Achilles' Heel on Privacy for Vision Transformers
Federated learning frameworks typically require collaborators to share t...
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10/12/2021
Improving Binary Neural Networks through Fully Utilizing Latent Weights
Binary Neural Networks (BNNs) rely on a real-valued auxiliary variable W...
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09/01/2021
Architecture Aware Latency Constrained Sparse Neural Networks
Acceleration of deep neural networks to meet a specific latency constrai...
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01/21/2021
Generative Zero-shot Network Quantization
Convolutional neural networks are able to learn realistic image priors f...
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09/15/2020
AIM 2020 Challenge on Efficient Super-Resolution: Methods and Results
This paper reviews the AIM 2020 challenge on efficient single image supe...
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11/13/2019
Location-aware Upsampling for Semantic Segmentation
Many successful learning targets such as dice loss and cross-entropy los...
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10/19/2019
SpatialFlow: Bridging All Tasks for Panoptic Segmentation
The newly proposed panoptic segmentation task, which aims to encompass t...
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09/24/2019
A System-Level Solution for Low-Power Object Detection
Object detection has made impressive progress in recent years with the h...
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07/23/2019
Compact Global Descriptor for Neural Networks
Long-range dependencies modeling, widely used in capturing spatiotempora...
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09/04/2018
