396 citations · 722 across the 10 of their papers we have counts for
8 papers · 1 filter
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…
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…