292 citations · 825 across the 13 of their papers we have counts for
13 papers
DiffCollage: Parallel Generation of Large Content with Diffusion Models
Qinsheng Zhang, Jiaming Song, Xun Huang +2
We present DiffCollage, a compositional diffusion model that can generate large content by leveraging diffusion models trained on generating pieces of the large content. Our approa…
Magic3D: High-Resolution Text-to-3D Content Creation
Chen-Hsuan Lin, Jun Gao, Luming Tang +7
DreamFusion has recently demonstrated the utility of a pre-trained text-to-image diffusion model to optimize Neural Radiance Fields (NeRF), achieving remarkable text-to-3D synthesi…
eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers
Yogesh Balaji, Seungjun Nah, Xun Huang +10
Large-scale diffusion-based generative models have led to breakthroughs in text-conditioned high-resolution image synthesis. Starting from random noise, such text-to-image diffusio…
Multimodal Conditional Image Synthesis with Product-of-Experts GANs
Xun Huang, Arun Mallya, Ting-Chun Wang +1
Existing conditional image synthesis frameworks generate images based on user inputs in a single modality, such as text, segmentation, sketch, or style reference. They are often un…
Generative Adversarial Networks for Image and Video Synthesis: Algorithms and Applications
Ming-Yu Liu, Xun Huang, Jiahui Yu +2
The generative adversarial network (GAN) framework has emerged as a powerful tool for various image and video synthesis tasks, allowing the synthesis of visual content in an uncond…
PointFlow: 3D Point Cloud Generation with Continuous Normalizing Flows
Guandao Yang, Xun Huang, Zekun Hao +3
As 3D point clouds become the representation of choice for multiple vision and graphics applications, the ability to synthesize or reconstruct high-resolution, high-fidelity point…
Few-Shot Unsupervised Image-to-Image Translation
Ming-Yu Liu, Xun Huang, Arun Mallya +4
Unsupervised image-to-image translation methods learn to map images in a given class to an analogous image in a different class, drawing on unstructured (non-registered) datasets o…
Learning to Evaluate Image Captioning
Yin Cui, Guandao Yang, Andreas Veit +2
Evaluation metrics for image captioning face two challenges. Firstly, commonly used metrics such as CIDEr, METEOR, ROUGE and BLEU often do not correlate well with human judgments.…
Multimodal Unsupervised Image-to-Image Translation
Xun Huang, Ming-Yu Liu, Serge Belongie +1
Unsupervised image-to-image translation is an important and challenging problem in computer vision. Given an image in the source domain, the goal is to learn the conditional distri…
Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization
Xun Huang, Serge Belongie
Gatys et al. recently introduced a neural algorithm that renders a content image in the style of another image, achieving so-called style transfer. However, their framework require…
Stacked Generative Adversarial Networks
Xun Huang, Yixuan Li, Omid Poursaeed +2
In this paper, we propose a novel generative model named Stacked Generative Adversarial Networks (SGAN), which is trained to invert the hierarchical representations of a bottom-up…
Top-Down Learning for Structured Labeling with Convolutional Pseudoprior
Saining Xie, Xun Huang, Zhuowen Tu
Current practice in convolutional neural networks (CNN) remains largely bottom-up and the role of top-down process in CNN for pattern analysis and visual inference is not very clea…
Learning of Proto-object Representations via Fixations on Low Resolution
Chengyao Shen, Xun Huang, Qi Zhao
While previous researches in eye fixation prediction typically rely on integrating low-level features (e.g. color, edge) to form a saliency map, recently it has been found that the…