EIDT-V: Exploiting Intersections in Diffusion Trajectories for Model-Agnostic, Zero-Shot, Training-Free Text-to-Video Generation
Diljeet Jagpal, Xi Chen, Vinay P. Namboodiri
2025年份
摘要
Eight equally spaced frames from 24-frame GIFs generated by our EIDT-V model. Top row shows SD3 Medium [8] results for prompt: "A peacock displaying its feathers". Bottom row shows SDXL [32] results for prompt: "A child blowing bubbles that float and pop gently". These examples highlight the model's ability to generate high-quality videos with semantic and temporal coherence.
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它引用的顶会 Paper22
- Language Models are Few-Shot LearnersTom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah 等NeurIPS 2020 · 被引用 64,255 次
- Learning Transferable Visual Models From Natural Language SupervisionAlec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh 等ICML 2021 · 被引用 47,906 次
- Denoising Diffusion Probabilistic ModelsJonathan Ho, Ajay Jain, Pieter AbbeelNeurIPS 2020 · 被引用 35,902 次
- Diffusion Models Beat GANs on Image SynthesisPrafulla Dhariwal, Alexander Quinn NicholNeurIPS 2021 · 被引用 13,211 次
- High-Resolution Image Synthesis with Latent Diffusion ModelsRobin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser 等CVPR 2022 · 被引用 13,123 次
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