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07/03/2023
SSC3OD: Sparsely Supervised Collaborative 3D Object Detection from LiDAR Point Clouds
Collaborative 3D object detection, with its improved interaction advanta...
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10/08/2022
Leveraging progressive model and overfitting for efficient learned image compression
Deep learning is overwhelmingly dominant in the field of computer vision...
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06/23/2022
LightFR: Lightweight Federated Recommendation with Privacy-preserving Matrix Factorization
Federated recommender system (FRS), which enables many local devices to ...
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12/16/2021
Adaptation and Attention for Neural Video Coding
Neural image coding represents now the state-of-the-art image compressio...
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08/24/2021
Lossless Image Compression Using a Multi-Scale Progressive Statistical Model
Lossless image compression is an important technique for image storage a...
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08/23/2021
Image coding for machines: an end-to-end learned approach
Over recent years, deep learning-based computer vision systems have been...
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08/23/2021
Learned Image Coding for Machines: A Content-Adaptive Approach
Today, according to the Cisco Annual Internet Report (2018-2023), the fa...
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05/26/2021
Adversarial Attack Framework on Graph Embedding Models with Limited Knowledge
With the success of the graph embedding model in both academic and indus...
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02/08/2021
Mask-GVAE: Blind Denoising Graphs via Partition
We present Mask-GVAE, a variational generative model for blind denoising...
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11/21/2020
Robust Watermarking Using Inverse Gradient Attention
Watermarking is the procedure of encoding desired information into an im...
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10/09/2020
Dirichlet Graph Variational Autoencoder
Graph Neural Networks (GNNs) and Variational Autoencoders (VAEs) have be...
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07/31/2020
L^2C – Learning to Learn to Compress
In this paper we present an end-to-end meta-learned system for image com...
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04/20/2020
End-to-End Learning for Video Frame Compression with Self-Attention
One of the core components of conventional (i.e., non-learned) video cod...
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01/22/2020
Adversarial Attack on Community Detection by Hiding Individuals
It has been demonstrated that adversarial graphs, i.e., graphs with impe...
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08/04/2019
A Restricted Black-box Adversarial Framework Towards Attacking Graph Embedding Models
With the great success of graph embedding model on both academic and ind...
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08/04/2019
The General Black-box Attack Method for Graph Neural Networks
With the great success of Graph Neural Networks (GNNs) towards represent...
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09/10/2018