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Pose-Aware Diffusion for 3D Generation
Zihan Zhou, Luxi Chen, Jingzhi Zhou +4
Generating pose-aligned 3D objects is challenging due to the spatial mismatches and transformation ambiguities inherent in decoupled canonical-then-rotate paradigms. To this end, w…
Bringing Your Portrait to 3D Presence
Jiawei Zhang, Lei Chu, Jiahao Li +6
We present a unified framework for reconstructing animatable 3D human avatars from a single portrait across head, half-body, and full-body inputs. Our method tackles three bottlene…
FlexWorld: Progressively Expanding 3D Scenes for Flexiable-View Synthesis
Luxi Chen, Zihan Zhou, Min Zhao +6
Generating flexible-view 3D scenes, including 360° rotation and zooming, from single images is challenging due to a lack of 3D data. To this end, we introduce FlexWorld, a novel fr…
Concat-ID: Towards Universal Identity-Preserving Video Synthesis
Yong Zhong, Zhuoyi Yang, Jiayan Teng +2
We present Concat-ID, a unified framework for identity-preserving video generation. Concat-ID employs variational autoencoders to extract image features, which are then concatenate…
Effective and Efficient Masked Image Generation Models
Zebin You, Jingyang Ou, Xiaolu Zhang +3
Although masked image generation models and masked diffusion models are designed with different motivations and objectives, we observe that they can be unified within a single fram…
Are Images Indistinguishable to Humans Also Indistinguishable to Classifiers?
Zebin You, Xinyu Zhang, Hanzhong Guo +2
The ultimate goal of generative models is to perfectly capture the data distribution. For image generation, common metrics of visual quality (e.g., FID) and the perceived truthfuln…
PoseCrafter: One-Shot Personalized Video Synthesis Following Flexible Pose Control
Yong Zhong, Min Zhao, Zebin You +3
In this paper, we introduce PoseCrafter, a one-shot method for personalized video generation following the control of flexible poses. Built upon Stable Diffusion and ControlNet, we…