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EM-Vid: Training-Free Entity-Centric Memory for Efficient and Consistent Multi-Shot Video Generation
Jente Vandersanden, Matheus Gadelha, Chun-Hao P. Huang +2
Multi-shot video generation requires maintaining a consistent appearance of recurring entities across shots while remaining faithful to shot-specific text prompts. Recent autoregre…
LoST: Level of Semantics Tokenization for 3D Shapes
Niladri Shekhar Dutt, Zifan Shi, Paul Guerrero +4
Tokenization is a fundamental technique in the generative modeling of various modalities. In particular, it plays a critical role in autoregressive (AR) models, which have recently…
TrajectoryMover: Generative Movement of Object Trajectories in Videos
Kiran Chhatre, Hyeonho Jeong, Yulia Gryaditskaya +3
Generative video editing has enabled creative control over an object's position in a video by prescribing an object's 3D or 2D motion trajectory, while preserving both video plausi…
Memory-V2V: Memory-Augmented Video-to-Video Diffusion for Consistent Multi-Turn Editing
Dohun Lee, Chun-Hao Paul Huang, Xuelin Chen +3
Video-to-video diffusion models achieve impressive single-turn editing performance, but practical editing workflows are inherently iterative. When edits are applied sequentially, e…