85 citations · 482 across the 58 of their papers we have counts for
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Scaling Laws For Diffusion Transformers
Zhengyang Liang, Hao He, Ceyuan Yang +1
Diffusion transformers (DiT) have already achieved appealing synthesis and scaling properties in content recreation, e.g., image and video generation. However, scaling laws of DiT…
3DitScene: Editing Any Scene via Language-guided Disentangled Gaussian Splatting
Qihang Zhang, Yinghao Xu, Chaoyang Wang +4
Scene image editing is crucial for entertainment, photography, and advertising design. Existing methods solely focus on either 2D individual object or 3D global scene editing. This…
CameraCtrl: Enabling Camera Control for Text-to-Video Generation
Hao He, Yinghao Xu, Yuwei Guo +4
Controllability plays a crucial role in video generation, as it allows users to create and edit content more precisely. Existing models, however, lack control of camera pose that s…
GRM: Large Gaussian Reconstruction Model for Efficient 3D Reconstruction and Generation
Yinghao Xu, Zifan Shi, Wang Yifan +5
We introduce GRM, a large-scale reconstructor capable of recovering a 3D asset from sparse-view images in around 0.1s. GRM is a feed-forward transformer-based model that efficientl…