research
∙
07/24/2023
CLIP-KD: An Empirical Study of Distilling CLIP Models
CLIP has become a promising language-supervised visual pre-training fram...
share
research
∙
06/19/2023
Categories of Response-Based, Feature-Based, and Relation-Based Knowledge Distillation
Deep neural networks have achieved remarkable performance for artificial...
research
∙
06/15/2023
Team AcieLee: Technical Report for EPIC-SOUNDS Audio-Based Interaction Recognition Challenge 2023
In this report, we describe the technical details of our submission to t...
research
∙
04/20/2023
eTag: Class-Incremental Learning with Embedding Distillation and Task-Oriented Generation
Class-Incremental Learning (CIL) aims to solve the neural networks' cata...
research
∙
08/11/2022
MixSKD: Self-Knowledge Distillation from Mixup for Image Recognition
Unlike the conventional Knowledge Distillation (KD), Self-KD allows a ne...
research
∙
07/23/2022
Online Knowledge Distillation via Mutual Contrastive Learning for Visual Recognition
The teacher-free online Knowledge Distillation (KD) aims to train an ens...
research
∙
06/07/2022
Localizing Semantic Patches for Accelerating Image Classification
Existing works often focus on reducing the architecture redundancy for a...
research
∙
04/14/2022
Cross-Image Relational Knowledge Distillation for Semantic Segmentation
Current Knowledge Distillation (KD) methods for semantic segmentation of...
research
∙
01/17/2022
Lifelong Generative Learning via Knowledge Reconstruction
Generative models often incur the catastrophic forgetting problem when t...
research
∙
09/07/2021
Knowledge Distillation Using Hierarchical Self-Supervision Augmented Distribution
Knowledge distillation (KD) is an effective framework that aims to trans...
research
∙
08/11/2021
A Channel-Aware Routing Protocol With Nearest Neighbor Regression For Underwater Sensor Networks
The underwater acoustic channel is one of the most challenging communica...
research
∙
07/29/2021
Hierarchical Self-supervised Augmented Knowledge Distillation
Knowledge distillation often involves how to define and transfer knowled...
research
∙
04/26/2021
Mutual Contrastive Learning for Visual Representation Learning
We present a collaborative learning method called Mutual Contrastive Lea...
research
∙
11/06/2020
GHFP: Gradually Hard Filter Pruning
Filter pruning is widely used to reduce the computation of deep learning...
research
∙
10/19/2020
Softer Pruning, Incremental Regularization
Network pruning is widely used to compress Deep Neural Networks (DNNs). ...
research
∙
06/07/2020
Multi-view Contrastive Learning for Online Knowledge Distillation
Existing Online Knowledge Distillation (OKD) aims to perform collaborati...
research
∙
01/31/2020
Localizing Multi-scale Semantic Patches for Image Classification
Deep convolutional neural networks (CNN) always non-linearly aggregate t...
research
∙
01/19/2020
Towards More Efficient and Effective Inference: The Joint Decision of Multi-Participants
Existing approaches to improve the performances of convolutional neural ...
research
∙
11/20/2019
DRNet: Dissect and Reconstruct the Convolutional Neural Network via Interpretable Manners
This paper proposes to use an interpretable method to dissect the channe...
research
∙
09/04/2019
Rethinking the Number of Channels for the Convolutional Neural Network
Latest algorithms for automatic neural architecture search perform remar...
research
∙
08/26/2019
Gated Convolutional Networks with Hybrid Connectivity for Image Classification
We design a highly efficient architecture called Gated Convolutional Net...
research
∙
06/02/2019
Multi-objective Pruning for CNNs using Genetic Algorithm
In this work, we propose a heuristic genetic algorithm (GA) for pruning ...
research
∙
05/10/2019
