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Found 4 papers, 2 papers with code
Motion Inversion for Video Customization
In this research, we present a novel approach to motion customization in video generation, addressing the widespread gap in the thorough exploration of motion representation within video generative models.
Decompose and Realign: Tackling Condition Misalignment in Text-to-Image Diffusion Models
The ``Decompose'' phase separates conditions based on pair relationships, computing the result individually for each pair.
LHNN: Lattice Hypergraph Neural Network for VLSI Congestion Prediction
Precise congestion prediction from a placement solution plays a crucial role in circuit placement.
GeoBi-GNN: Geometry-aware Bi-domain Mesh Denoising via Graph Neural Networks
For the first time, we optimize both positions and normals (i. e., dual domains) in a unified framework of GNN, and show the powerful inter-coordination between the dual domains.
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