1 citations · 1 across the 6 of their papers we have counts for
6 papers
FaithfulFaces: Pose-Faithful Facial Identity Preservation for Text-to-Video Generation
Yuanzhi Wang, Xuhua Ren, Jiaxiang Cheng +7
Identity-preserving text-to-video generation (IPT2V) empowers users to produce diverse and imaginative videos with consistent human facial identity. Despite recent progress, existi…
Threshold-Guided Optimization for Visual Generative Models
Jinbin Bai, Yu Lei, Qingyu Shi +6
Aligning large visual generative models with human feedback is often performed through pairwise preference optimization. While such approaches are conceptually simple, they fundame…
Disentangling Foreground and Background Motion for Enhanced Realism in Human Video Generation
Jinlin Liu, Kai Yu, Mengyang Feng +2
Recent advancements in human video synthesis have enabled the generation of high-quality videos through the application of stable diffusion models. However, existing methods predom…
DreaMoving: A Human Video Generation Framework based on Diffusion Models
Mengyang Feng, Jinlin Liu, Kai Yu +13
In this paper, we present DreaMoving, a diffusion-based controllable video generation framework to produce high-quality customized human videos. Specifically, given target identity…
DiffusionGAN3D: Boosting Text-guided 3D Generation and Domain Adaptation by Combining 3D GANs and Diffusion Priors
Biwen Lei, Kai Yu, Mengyang Feng +2
Text-guided domain adaptation and generation of 3D-aware portraits find many applications in various fields. However, due to the lack of training data and the challenges in handlin…
Boosting3D: High-Fidelity Image-to-3D by Boosting 2D Diffusion Prior to 3D Prior with Progressive Learning
Kai Yu, Jinlin Liu, Mengyang Feng +2
We present Boosting3D, a multi-stage single image-to-3D generation method that can robustly generate reasonable 3D objects in different data domains. The point of this work is to s…