4 papers
PE-Field 4D: Video Generation Models as Canvas
Yunpeng Bai, Haoxiang Li, Qixing Huang
Diffusion Transformers have recently achieved strong performance in video generation, yet controlling scene geometry under viewpoint changes and camera motion remains challenging.…
UniLayDiff: A Unified Diffusion Transformer for Content-Aware Layout Generation
Zeyang Liu, Le Wang, Sanping Zhou +4
Content-aware layout generation is a critical task in graphic design automation, focused on creating visually appealing arrangements of elements that seamlessly blend with a given…
LayoutRAG: Retrieval-Augmented Model for Content-agnostic Conditional Layout Generation
Yuxuan Wu, Le Wang, Sanping Zhou +3
Controllable layout generation aims to create plausible visual arrangements of element bounding boxes within a graphic design according to certain optional constraints, such as the…
Glissando-Net: Deep sinGLe vIew category level poSe eStimation ANd 3D recOnstruction
Bo Sun, Hao Kang, Li Guan +3
We present a deep learning model, dubbed Glissando-Net, to simultaneously estimate the pose and reconstruct the 3D shape of objects at the category level from a single RGB image. P…