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Found 5 papers, 0 papers with code
How to Understand Named Entities: Using Common Sense for News Captioning
Our approach consists of three modules: (a) Filter Module aims to clarify the common sense concerning a named entity from two aspects: what does it mean?
ART$\boldsymbol{\cdot}$V: Auto-Regressive Text-to-Video Generation with Diffusion Models
Second, it preserves the high-fidelity generation ability of the pre-trained image diffusion models by making only minimal network modifications.
MicroCinema: A Divide-and-Conquer Approach for Text-to-Video Generation
We present MicroCinema, a straightforward yet effective framework for high-quality and coherent text-to-video generation.
Panacea: Panoramic and Controllable Video Generation for Autonomous Driving
This work notably propels the field of autonomous driving by effectively augmenting the training dataset used for advanced BEV perception techniques.
CCEdit: Creative and Controllable Video Editing via Diffusion Models
The versatility of our framework is demonstrated through a diverse range of choices in both structure representations and personalized T2I models, as well as the option to provide the edited key frame.
