9 papers
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…
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…
LLaDA2.0: Scaling Up Diffusion Language Models to 100B
Tiwei Bie, Maosong Cao, Kun Chen +28
This paper presents LLaDA2.0 -- a tuple of discrete diffusion large language models (dLLM) scaling up to 100B total parameters through systematic conversion from auto-regressive (A…
LLaDA-MoE: A Sparse MoE Diffusion Language Model
Fengqi Zhu, Zebin You, Yipeng Xing +23
We introduce LLaDA-MoE, a large language diffusion model with the Mixture-of-Experts (MoE) architecture, trained from scratch on approximately 20T tokens. LLaDA-MoE achieves compet…
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…