34 citations · 56 across the 23 of their papers we have counts for
24 papers
4DHumanDiff: Direct Text-to-4DGS Generation for Consistent 360-Degree Dynamic Humans
Renlong Wu, Haoran Chen, Yuxiang Wei +3
Generating high-quality 360-degree dynamic human assets from text prompts is challenging. Existing methods usually synthesize monocular or multi-view videos first and then fit a 4D…
Premier: Personalized Preference Modulation with Learnable User Embedding in Text-to-Image Generation
Zihao Wang, Yuxiang Wei, Xinpeng Zhou +5
Text-to-image generation has advanced rapidly, yet it still struggles to capture the nuanced user preferences. Existing approaches typically rely on multimodal large language model…
DreamLite: A Lightweight On-Device Unified Model for Image Generation and Editing
Kailai Feng, Yuxiang Wei, Bo Chen +5
Diffusion models have made significant progress in both text-to-image (T2I) generation and text-guided image editing. However, these models are typically built with billions of par…
CREval: An Automated Interpretable Evaluation for Creative Image Manipulation under Complex Instructions
Chonghuinan Wang, Zihan Chen, Yuxiang Wei +5
Instruction-based multimodal image manipulation has recently made rapid progress. However, existing evaluation methods lack a systematic and human-aligned framework for assessing m…
CoEditor++: Instruction-based Visual Editing via Cognitive Reasoning
Minheng Ni, Yutao Fan, Zhengyuan Yang +6
Recent advances in large multimodal models (LMMs) have enabled instruction-based image editing, allowing users to modify visual content via natural language descriptions. However,…
EfficientMT: Efficient Temporal Adaptation for Motion Transfer in Text-to-Video Diffusion Models
Yufei Cai, Hu Han, Yuxiang Wei +2
The progress on generative models has led to significant advances on text-to-video (T2V) generation, yet the motion controllability of generated videos remains limited. Existing mo…
Personalized Image Generation with Deep Generative Models: A Decade Survey
Yuxiang Wei, Yiheng Zheng, Yabo Zhang +4
Recent advancements in generative models have significantly facilitated the development of personalized content creation. Given a small set of images with user-specific concept, pe…
ACE: Anti-Editing Concept Erasure in Text-to-Image Models
Zihao Wang, Yuxiang Wei, Fan Li +3
Recent advance in text-to-image diffusion models have significantly facilitated the generation of high-quality images, but also raising concerns about the illegal creation of harmf…
ScaleDreamer: Scalable Text-to-3D Synthesis with Asynchronous Score Distillation
Zhiyuan Ma, Yuxiang Wei, Yabin Zhang +3
By leveraging the text-to-image diffusion priors, score distillation can synthesize 3D contents without paired text-3D training data. Instead of spending hours of online optimizati…
MasterWeaver: Taming Editability and Face Identity for Personalized Text-to-Image Generation
Yuxiang Wei, Zhilong Ji, Jinfeng Bai +3
Text-to-image (T2I) diffusion models have shown significant success in personalized text-to-image generation, which aims to generate novel images with human identities indicated by…
SmartControl: Enhancing ControlNet for Handling Rough Visual Conditions
Xiaoyu Liu, Yuxiang Wei, Ming Liu +4
Human visual imagination usually begins with analogies or rough sketches. For example, given an image with a girl playing guitar before a building, one may analogously imagine how…
VideoElevator: Elevating Video Generation Quality with Versatile Text-to-Image Diffusion Models
Yabo Zhang, Yuxiang Wei, Xianhui Lin +5
Text-to-image diffusion models (T2I) have demonstrated unprecedented capabilities in creating realistic and aesthetic images. On the contrary, text-to-video diffusion models (T2V)…
PLACE: Adaptive Layout-Semantic Fusion for Semantic Image Synthesis
Zhengyao Lv, Yuxiang Wei, Wangmeng Zuo +1
Recent advancements in large-scale pre-trained text-to-image models have led to remarkable progress in semantic image synthesis. Nevertheless, synthesizing high-quality images with…
Improving Image Restoration through Removing Degradations in Textual Representations
Jingbo Lin, Zhilu Zhang, Yuxiang Wei +3
In this paper, we introduce a new perspective for improving image restoration by removing degradation in the textual representations of a given degraded image. Intuitively, restora…
Black-Box Tuning of Vision-Language Models with Effective Gradient Approximation
Zixian Guo, Yuxiang Wei, Ming Liu +4
Parameter-efficient fine-tuning (PEFT) methods have provided an effective way for adapting large vision-language models to specific tasks or scenarios. Typically, they learn a very…
Decoupled Textual Embeddings for Customized Image Generation
Yufei Cai, Yuxiang Wei, Zhilong Ji +3
Customized text-to-image generation, which aims to learn user-specified concepts with a few images, has drawn significant attention recently. However, existing methods usually suff…
Inferring and Leveraging Parts from Object Shape for Improving Semantic Image Synthesis
Yuxiang Wei, Zhilong Ji, Xiaohe Wu +3
Despite the progress in semantic image synthesis, it remains a challenging problem to generate photo-realistic parts from input semantic map. Integrating part segmentation map can…
ControlVideo: Training-free Controllable Text-to-Video Generation
Yabo Zhang, Yuxiang Wei, Dongsheng Jiang +3
Text-driven diffusion models have unlocked unprecedented abilities in image generation, whereas their video counterpart still lags behind due to the excessive training cost of temp…
ELITE: Encoding Visual Concepts into Textual Embeddings for Customized Text-to-Image Generation
Yuxiang Wei, Yabo Zhang, Zhilong Ji +3
In addition to the unprecedented ability in imaginary creation, large text-to-image models are expected to take customized concepts in image generation. Existing works generally le…
A Survey on Leveraging Pre-trained Generative Adversarial Networks for Image Editing and Restoration
Ming Liu, Yuxiang Wei, Xiaohe Wu +2
Generative adversarial networks (GANs) have drawn enormous attention due to the simple yet effective training mechanism and superior image generation quality. With the ability to g…
Towards Diverse and Faithful One-shot Adaption of Generative Adversarial Networks
Yabo Zhang, Mingshuai Yao, Yuxiang Wei +3
One-shot generative domain adaption aims to transfer a pre-trained generator on one domain to a new domain using one reference image only. However, it remains very challenging for…
Retrieval-based Spatially Adaptive Normalization for Semantic Image Synthesis
Yupeng Shi, Xiao Liu, Yuxiang Wei +2
Semantic image synthesis is a challenging task with many practical applications. Albeit remarkable progress has been made in semantic image synthesis with spatially-adaptive normal…
Orthogonal Jacobian Regularization for Unsupervised Disentanglement in Image Generation
Yuxiang Wei, Yupeng Shi, Xiao Liu +4
Unsupervised disentanglement learning is a crucial issue for understanding and exploiting deep generative models. Recently, SeFa tries to find latent disentangled directions by per…
Learning Flow-based Feature Warping for Face Frontalization with Illumination Inconsistent Supervision
Yuxiang Wei, Ming Liu, Haolin Wang +3
Despite recent advances in deep learning-based face frontalization methods, photo-realistic and illumination preserving frontal face synthesis is still challenging due to large pos…