65 citations · 79 across the 13 of their papers we have counts for
13 papers · 1 filter
LooC: Effective Low-Dimensional Codebook for Compositional Vector Quantization
Jie Li, Kwan-Yee K. Wong, Kai Han
Vector quantization (VQ) is a prevalent and fundamental technique that discretizes continuous feature vectors by approximating them using a codebook. As the diversity and complexit…
VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models
Chaohao Xie, Kai Han, Kwan-Yee K. Wong
Recent video inpainting methods have achieved encouraging improvements by leveraging optical flow to guide pixel propagation from reference frames either in the image space or feat…
AvatarGO: Zero-shot 4D Human-Object Interaction Generation and Animation
Yukang Cao, Liang Pan, Kai Han +2
Recent advancements in diffusion models have led to significant improvements in the generation and animation of 4D full-body human-object interactions (HOI). Nevertheless, existing…
BiGR: Harnessing Binary Latent Codes for Image Generation and Improved Visual Representation Capabilities
Shaozhe Hao, Xuantong Liu, Xianbiao Qi +5
We introduce BiGR, a novel conditional image generation model using compact binary latent codes for generative training, focusing on enhancing both generation and representation ca…
ArtiFade: Learning to Generate High-quality Subject from Blemished Images
Shuya Yang, Shaozhe Hao, Yukang Cao +1
Subject-driven text-to-image generation has witnessed remarkable advancements in its ability to learn and capture characteristics of a subject using only a limited number of images…
A Survey on 3D Human Avatar Modeling -- From Reconstruction to Generation
Ruihe Wang, Yukang Cao, Kai Han +1
3D modeling has long been an important area in computer vision and computer graphics. Recently, thanks to the breakthroughs in neural representations and generative models, we witn…
Bridging Different Language Models and Generative Vision Models for Text-to-Image Generation
Shihao Zhao, Shaozhe Hao, Bojia Zi +2
Text-to-image generation has made significant advancements with the introduction of text-to-image diffusion models. These models typically consist of a language model that interpre…
Guide3D: Create 3D Avatars from Text and Image Guidance
Yukang Cao, Yan-Pei Cao, Kai Han +2
Recently, text-to-image generation has exhibited remarkable advancements, with the ability to produce visually impressive results. In contrast, text-to-3D generation has not yet re…
RIGID: Recurrent GAN Inversion and Editing of Real Face Videos
Yangyang Xu, Shengfeng He, Kwan-Yee K. Wong +1
GAN inversion is indispensable for applying the powerful editability of GAN to real images. However, existing methods invert video frames individually often leading to undesired in…
HeadSculpt: Crafting 3D Head Avatars with Text
Xiao Han, Yukang Cao, Kai Han +5
Recently, text-guided 3D generative methods have made remarkable advancements in producing high-quality textures and geometry, capitalizing on the proliferation of large vision-lan…
ViCo: Plug-and-play Visual Condition for Personalized Text-to-image Generation
Shaozhe Hao, Kai Han, Shihao Zhao +1
Personalized text-to-image generation using diffusion models has recently emerged and garnered significant interest. This task learns a novel concept (e.g., a unique toy), illustra…
Uni-ControlNet: All-in-One Control to Text-to-Image Diffusion Models
Shihao Zhao, Dongdong Chen, Yen-Chun Chen +4
Text-to-Image diffusion models have made tremendous progress over the past two years, enabling the generation of highly realistic images based on open-domain text descriptions. How…
CiPR: An Efficient Framework with Cross-instance Positive Relations for Generalized Category Discovery
Shaozhe Hao, Kai Han, Kwan-Yee K. Wong
We tackle the issue of generalized category discovery (GCD). GCD considers the open-world problem of automatically clustering a partially labelled dataset, in which the unlabelled…