43 citations · 90 across the 10 of their papers we have counts for
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cs.GR2025
RealMat: Realistic Materials with Diffusion and Reinforcement Learning
Xilong Zhou, Pedro Figueiredo, Miloš Hašan +4
Generative models for high-quality materials are particularly desirable to make 3D content authoring more accessible. However, the majority of material generation methods are train…
cs.CV2025
HiMat: DiT-based Ultra-High Resolution SVBRDF Generation
Zixiong Wang, Jian Yang, Yiwei Hu +2
Creating ultra-high-resolution spatially varying bidirectional reflectance functions (SVBRDFs) is critical for photorealistic 3D content creation, to faithfully represent fine-scal…
cs.CV2025
OmniVCus: Feedforward Subject-driven Video Customization with Multimodal Control Conditions
Yuanhao Cai, He Zhang, Xi Chen +11
Existing feedforward subject-driven video customization methods mainly study single-subject scenarios due to the difficulty of constructing multi-subject training data pairs. Anoth…