A single motion module trained on videos adds temporally coherent animation to any personalized text-to-image model derived from the same base without additional tuning.
Instantbooth: Personalized text-to-image generation without test-time finetuning
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Equilibrated Diffusion decomposes concepts in frequency space to independently optimize subject and style embeddings, plus mask-guided diffusion and residual reference attention, for improved subject fidelity and text alignment over baselines.
Open-source text-to-video and image-to-video diffusion models generate high-quality 1024x576 videos, with the I2V variant claimed as the first to strictly preserve reference image content.
SOW uses MLLMs and attention to selectively control unidirectional diffusion for pixel-level fidelity and contextual coherence in text-vision-to-image tasks.
citing papers explorer
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AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning
A single motion module trained on videos adds temporally coherent animation to any personalized text-to-image model derived from the same base without additional tuning.
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Equilibrated Diffusion: Frequency-aware Textual Embedding for Equilibrated Image Customization
Equilibrated Diffusion decomposes concepts in frequency space to independently optimize subject and style embeddings, plus mask-guided diffusion and residual reference attention, for improved subject fidelity and text alignment over baselines.
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VideoCrafter1: Open Diffusion Models for High-Quality Video Generation
Open-source text-to-video and image-to-video diffusion models generate high-quality 1024x576 videos, with the I2V variant claimed as the first to strictly preserve reference image content.
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SOWing Information: Cultivating Contextual Coherence with MLLMs in Image Generation
SOW uses MLLMs and attention to selectively control unidirectional diffusion for pixel-level fidelity and contextual coherence in text-vision-to-image tasks.