396 citations · 722 across the 10 of their papers we have counts for
11 papers
Design Automation for Gray-Code Quantum Read-Only Memory
Hao-Yu Lu, Yu-Ting Kao, Yeong-Jar Chang +2
We propose a programmable quantum read-only memory based on Gray code encoding, termed GQROM, designed to efficiently load classical data into quantum circuits. This architecture m…
MM-TRELLIS: Point-Cloud Guided Multi-Modal 3D Vehicle Generation in Autonomous Driving
Hongli Xiao, Youjian Zhang, Yucai Bai +5
Recovering realistic 3D vehicle models from autonomous driving scenes is crucial for synthesizing training data and building simulation environment. However, most existing vehicle…
PartSeg: Few-shot Part Segmentation via Part-aware Prompt Learning
Mengya Han, Heliang Zheng, Chaoyue Wang +4
In this work, we address the task of few-shot part segmentation, which aims to segment the different parts of an unseen object using very few labeled examples. It is found that lev…
Null-text Guidance in Diffusion Models is Secretly a Cartoon-style Creator
Jing Zhao, Heliang Zheng, Chaoyue Wang +3
Classifier-free guidance is an effective sampling technique in diffusion models that has been widely adopted. The main idea is to extrapolate the model in the direction of text gui…
MagicFusion: Boosting Text-to-Image Generation Performance by Fusing Diffusion Models
Jing Zhao, Heliang Zheng, Chaoyue Wang +2
The advent of open-source AI communities has produced a cornucopia of powerful text-guided diffusion models that are trained on various datasets. While few explorations have been c…
Domain Re-Modulation for Few-Shot Generative Domain Adaptation
Yi Wu, Ziqiang Li, Chaoyue Wang +4
In this study, we delve into the task of few-shot Generative Domain Adaptation (GDA), which involves transferring a pre-trained generator from one domain to a new domain using only…
FakeCLR: Exploring Contrastive Learning for Solving Latent Discontinuity in Data-Efficient GANs
Ziqiang Li, Chaoyue Wang, Heliang Zheng +2
Data-Efficient GANs (DE-GANs), which aim to learn generative models with a limited amount of training data, encounter several challenges for generating high-quality samples. Since…
A Comprehensive Survey on Data-Efficient GANs in Image Generation
Ziqiang Li, Beihao Xia, Jing Zhang +2
Generative Adversarial Networks (GANs) have achieved remarkable achievements in image synthesis. These successes of GANs rely on large scale datasets, requiring too much cost. With…
Experimental Quantum Generative Adversarial Networks for Image Generation
He-Liang Huang, Yuxuan Du, Ming Gong +18
Quantum machine learning is expected to be one of the first practical applications of near-term quantum devices. Pioneer theoretical works suggest that quantum generative adversari…
Evolutionary Generative Adversarial Networks
Chaoyue Wang, Chang Xu, Xin Yao +1
Generative adversarial networks (GAN) have been effective for learning generative models for real-world data. However, existing GANs (GAN and its variants) tend to suffer from trai…
Perceptual Adversarial Networks for Image-to-Image Transformation
Chaoyue Wang, Chang Xu, Chaohui Wang +1
In this paper, we propose a principled Perceptual Adversarial Networks (PAN) for image-to-image transformation tasks. Unlike existing application-specific algorithms, PAN provides…