103 citations · 222 across the 23 of their papers we have counts for
27 papers
BTC3D: Blended Tile Conditioning for Detail-Enhancing Image-to-3D Generation
Junyu Li, Qiuyu Chen, Pengcheng Wang +5
Recent diffusion-based pipelines have achieved promising progress in image-to-3D synthesis. However, generating high-fidelity details remains challenging, especially when the input…
AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling
Jiajun Liang, Yucheng Liao, Yukang Cao +12
Language remains an outlier in generative modeling: while images, video, and audio are increasingly modeled in continuous latent spaces, text generation still relies predominantly…
Training-free image inversion for one-step diffusion models
Tao Wu, Senmao Li, Yaxing Wang +3
In this work, we introduce a novel training-free inversion (TFinv) framework for one-step diffusion models,addressing key challenges in real image inversion and editing. We first i…
Adversarial Concept Distillation for One-Step Diffusion Personalization
Yixiong Yang, Tao Wu, Senmao Li +4
Recent progress in accelerating text-to-image diffusion models enables high-fidelity synthesis within a single denoising step. However, customizing the fast one-step models remains…
From Cradle to Cane: A Two-Pass Framework for High-Fidelity Lifespan Face Aging
Tao Liu, Dafeng Zhang, Gengchen Li +7
Face aging has become a crucial task in computer vision, with applications ranging from entertainment to healthcare. However, existing methods struggle with achieving a realistic a…
One-Way Ticket:Time-Independent Unified Encoder for Distilling Text-to-Image Diffusion Models
Senmao Li, Lei Wang, Kai Wang +7
Text-to-Image (T2I) diffusion models have made remarkable advancements in generative modeling; however, they face a trade-off between inference speed and image quality, posing chal…
InterLCM: Low-Quality Images as Intermediate States of Latent Consistency Models for Effective Blind Face Restoration
Senmao Li, Kai Wang, Joost van de Weijer +6
Diffusion priors have been used for blind face restoration (BFR) by fine-tuning diffusion models (DMs) on restoration datasets to recover low-quality images. However, the naive app…
Free-Lunch Color-Texture Disentanglement for Stylized Image Generation
Jiang Qin, Senmao Li, Alexandra Gomez-Villa +4
Recent advances in Text-to-Image (T2I) diffusion models have transformed image generation, enabling significant progress in stylized generation using only a few style reference ima…
One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt
Tao Liu, Kai Wang, Senmao Li +6
Text-to-image generation models can create high-quality images from input prompts. However, they struggle to support the consistent generation of identity-preserving requirements f…
SpecMaskGIT: Masked Generative Modeling of Audio Spectrograms for Efficient Audio Synthesis and Beyond
Marco Comunità, Zhi Zhong, Akira Takahashi +7
Recent advances in generative models that iteratively synthesize audio clips sparked great success to text-to-audio synthesis (TTA), but with the cost of slow synthesis speed and h…
Visual Echoes: A Simple Unified Transformer for Audio-Visual Generation
Shiqi Yang, Zhi Zhong, Mengjie Zhao +4
In recent years, with the realistic generation results and a wide range of personalized applications, diffusion-based generative models gain huge attention in both visual and audio…
Faster Diffusion: Rethinking the Role of the Encoder for Diffusion Model Inference
Senmao Li, Taihang Hu, Joost van de Weijer +7
One of the main drawback of diffusion models is the slow inference time for image generation. Among the most successful approaches to addressing this problem are distillation metho…
MaTe3D: Mask-guided Text-based 3D-aware Portrait Editing
Kangneng Zhou, Daiheng Gao, Xuan Wang +9
3D-aware portrait editing has a wide range of applications in multiple fields. However, current approaches are limited due that they can only perform mask-guided or text-based edit…
Dynamic Prompt Learning: Addressing Cross-Attention Leakage for Text-Based Image Editing
Kai Wang, Fei Yang, Shiqi Yang +2
Large-scale text-to-image generative models have been a ground-breaking development in generative AI, with diffusion models showing their astounding ability to synthesize convincin…
Trust your Good Friends: Source-free Domain Adaptation by Reciprocal Neighborhood Clustering
Shiqi Yang, Yaxing Wang, Joost van de Weijer +3
Domain adaptation (DA) aims to alleviate the domain shift between source domain and target domain. Most DA methods require access to the source data, but often that is not possible…
A Critical Look at the Current Usage of Foundation Model for Dense Recognition Task
Shiqi Yang, Atsushi Hashimoto, Yoshitaka Ushiku
In recent years large model trained on huge amount of cross-modality data, which is usually be termed as foundation model, achieves conspicuous accomplishment in many fields, such…
Positive Pair Distillation Considered Harmful: Continual Meta Metric Learning for Lifelong Object Re-Identification
Kai Wang, Chenshen Wu, Andy Bagdanov +4
Lifelong object re-identification incrementally learns from a stream of re-identification tasks. The objective is to learn a representation that can be applied to all tasks and tha…
OneRing: A Simple Method for Source-free Open-partial Domain Adaptation
Shiqi Yang, Yaxing Wang, Kai Wang +2
In this paper, we investigate Source-free Open-partial Domain Adaptation (SF-OPDA), which addresses the situation where there exist both domain and category shifts between source a…
Attracting and Dispersing: A Simple Approach for Source-free Domain Adaptation
Shiqi Yang, Yaxing Wang, Kai Wang +2
We propose a simple but effective source-free domain adaptation (SFDA) method. Treating SFDA as an unsupervised clustering problem and following the intuition that local neighbors…
Exploiting the Intrinsic Neighborhood Structure for Source-free Domain Adaptation
Shiqi Yang, Yaxing Wang, Joost van de Weijer +2
Domain adaptation (DA) aims to alleviate the domain shift between source domain and target domain. Most DA methods require access to the source data, but often that is not possible…
Generalized Source-free Domain Adaptation
Shiqi Yang, Yaxing Wang, Joost van de Weijer +2
Domain adaptation (DA) aims to transfer the knowledge learned from a source domain to an unlabeled target domain. Some recent works tackle source-free domain adaptation (SFDA) wher…
On Implicit Attribute Localization for Generalized Zero-Shot Learning
Shiqi Yang, Kai Wang, Luis Herranz +1
Zero-shot learning (ZSL) aims to discriminate images from unseen classes by exploiting relations to seen classes via their attribute-based descriptions. Since attributes are often…
Casting a BAIT for Offline and Online Source-free Domain Adaptation
Shiqi Yang, Yaxing Wang, Joost van de Weijer +2
We address the source-free domain adaptation (SFDA) problem, where only the source model is available during adaptation to the target domain. We consider two settings: the offline…
Simple and effective localized attribute representations for zero-shot learning
Shiqi Yang, Kai Wang, Luis Herranz +1
Zero-shot learning (ZSL) aims to discriminate images from unseen classes by exploiting relations to seen classes via their semantic descriptions. Some recent papers have shown the…