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Haoyu Wu

7 accepted papers

2026

Geometry Forcing: Marrying Video Diffusion and 3D Representation for Consistent World Modeling

ICLR 2026poster

Videos inherently represent 2D projections of a dynamic 3D world. However, our analysis suggests that video diffusion models trained solely on raw video data often fail to capture meaningful geometric-aware structure in their learned representations. To bridge this gap between video diffusion models…

Cited by 0SourcecodeScholar
2025

DualTalk: Dual-Speaker Interaction for 3D Talking Head Conversations

CVPR 2025poster

In face-to-face conversations, individuals need to switch between speaking and listening roles seamlessly. Existing 3D talking head generation models focus solely on speaking or listening, neglecting the natural dynamics of interactive conversation, which leads to unnatural interactions and awkward…

2025

Importance-Based Token Merging for Efficient Image and Video Generation

ICCV 2025poster

Token merging can effectively accelerate various vision systems by processing groups of similar tokens only once and sharing the results across them. However, existing token grouping methods are often ad hoc and random, disregarding the actual content of the samples. We show that preserving high-inf…

Cited by 0SourcePDFScholar
2025

VideoDPO: Omni-Preference Alignment for Video Diffusion Generation

CVPR 2025poster

Recent progress in generative diffusion models has greatly advanced text-to-video generation. While text-to-video models trained on large-scale, diverse datasets can produce varied outputs, these generations often deviate from user preferences, highlighting the need for preference alignment on pre-t…

2023

EmoTalk: Speech-Driven Emotional Disentanglement for 3D Face Animation

ICCV 2023poster

Speech-driven 3D face animation aims to generate realistic facial expressions that match the speech content and emotion. However, existing methods often neglect emotional facial expressions or fail to disentangle them from speech content. To address this issue, this paper proposes an end-to-end neur…

Cited by 117PDFcodeScholar
2023

S-VolSDF: Sparse Multi-View Stereo Regularization of Neural Implicit Surfaces

ICCV 2023poster

Neural rendering of implicit surfaces performs well in 3D vision applications. However, it requires dense input views as supervision. When only sparse input images are available, output quality drops significantly due to the shape-radiance ambiguity problem. We note that this ambiguity can be constr…

Cited by 18PDFScholar