activity
20142024
most citedComposer: Creative and Controllable Image Synthesis with Composable Conditions

52 citations · 191 across the 18 of their papers we have counts for

collaborators

18 papers

cs.LG202415 cited

Space Group Constrained Crystal Generation

Rui Jiao, Wenbing Huang, Yu Liu +2

Crystals are the foundation of numerous scientific and industrial applications. While various learning-based approaches have been proposed for crystal generation, existing methods…

cs.CV202322 cited

I2VGen-XL: High-Quality Image-to-Video Synthesis via Cascaded Diffusion Models

Shiwei Zhang, Jiayu Wang, Yingya Zhang +6

Video synthesis has recently made remarkable strides benefiting from the rapid development of diffusion models. However, it still encounters challenges in terms of semantic accurac…

cs.CV20234 cited

Res-Tuning: A Flexible and Efficient Tuning Paradigm via Unbinding Tuner from Backbone

Zeyinzi Jiang, Chaojie Mao, Ziyuan Huang +5

Parameter-efficient tuning has become a trend in transferring large-scale foundation models to downstream applications. Existing methods typically embed some light-weight tuners in…

cs.CV20231 cited

Efficient-VQGAN: Towards High-Resolution Image Generation with Efficient Vision Transformers

Shiyue Cao, Yueqin Yin, Lianghua Huang +4

Vector-quantized image modeling has shown great potential in synthesizing high-quality images. However, generating high-resolution images remains a challenging task due to the quad…

cs.CV2023

In-Domain GAN Inversion for Faithful Reconstruction and Editability

Jiapeng Zhu, Yujun Shen, Yinghao Xu +3

Generative Adversarial Networks (GANs) have significantly advanced image synthesis through mapping randomly sampled latent codes to high-fidelity synthesized images. However, apply…

cs.CV20232 cited

Disentangling Spatial and Temporal Learning for Efficient Image-to-Video Transfer Learning

Zhiwu Qing, Shiwei Zhang, Ziyuan Huang +4

Recently, large-scale pre-trained language-image models like CLIP have shown extraordinary capabilities for understanding spatial contents, but naively transferring such models to…