331 citations · 569 across the 47 of their papers we have counts for
49 papers · 1 filter
Lightweight Image Codec via Multi-Grid Multi-Block-Size Vector Quantization (MGBVQ)
Yifan Wang, Zhanxuan Mei, Ioannis Katsavounidis +1
A multi-grid multi-block-size vector quantization (MGBVQ) method is proposed for image coding in this work. The fundamental idea of image coding is to remove correlations among pix…
A-PixelHop: A Green, Robust and Explainable Fake-Image Detector
Yao Zhu, Xinyu Wang, Hong-Shuo Chen +2
A novel method for detecting CNN-generated images, called Attentive PixelHop (or A-PixelHop), is proposed in this work. It has three advantages: 1) low computational complexity and…
PEDENet: Image Anomaly Localization via Patch Embedding and Density Estimation
Kaitai Zhang, Bin Wang, C. -C. Jay Kuo
A neural network targeting at unsupervised image anomaly localization, called the PEDENet, is proposed in this work. PEDENet contains a patch embedding (PE) network, a density esti…
UHP-SOT: An Unsupervised High-Performance Single Object Tracker
Zhiruo Zhou, Hongyu Fu, Suya You +2
An unsupervised online object tracking method that exploits both foreground and background correlations is proposed and named UHP-SOT (Unsupervised High-Performance Single Object T…
BERTHop: An Effective Vision-and-Language Model for Chest X-ray Disease Diagnosis
Masoud Monajatipoor, Mozhdeh Rouhsedaghat, Liunian Harold Li +4
Vision-and-language(V&L) models take image and text as input and learn to capture the associations between them. Prior studies show that pre-trained V&L models can significantly im…
Adversarial Unsupervised Domain Adaptation with Conditional and Label Shift: Infer, Align and Iterate
Xiaofeng Liu, Zhenhua Guo, Site Li +5
In this work, we propose an adversarial unsupervised domain adaptation (UDA) approach with the inherent conditional and label shifts, in which we aim to align the distributions w.r…