QWERTY enables training-free motion control in pretrained image-to-video DiTs by warping the frame-invariant semantic subspace of queries in 3D full attention and using the predicted noise as self-guidance for latent optimization.
Fine- grained open domain image animation with motion guidance
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Fully aligned instructional videos for physical tasks yield 11.1% better completion quality and 15.5% faster times, with four decomposable visual attributes whose isolated misalignments degrade performance without users noticing.
Show-o2 unifies text, image, and video understanding and generation in a single autoregressive-plus-flow-matching model built on 3D causal VAE representations.
This survey traces video generation technology from GANs to diffusion models and then to autoregressive and multimodal approaches while analyzing principles, strengths, and future trends.
citing papers explorer
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QWERTY: Training-Free Motion Control via Query-Warped Video Diffusion Transformers
QWERTY enables training-free motion control in pretrained image-to-video DiTs by warping the frame-invariant semantic subspace of queries in 3D full attention and using the predicted noise as self-guidance for latent optimization.
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Substantial, Decomposable, and Invisible: Visual Context Misalignment in Instructional Videos for Physical Tasks
Fully aligned instructional videos for physical tasks yield 11.1% better completion quality and 15.5% faster times, with four decomposable visual attributes whose isolated misalignments degrade performance without users noticing.
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Show-o2: Improved Native Unified Multimodal Models
Show-o2 unifies text, image, and video understanding and generation in a single autoregressive-plus-flow-matching model built on 3D causal VAE representations.
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Evolution of Video Generative Foundations
This survey traces video generation technology from GANs to diffusion models and then to autoregressive and multimodal approaches while analyzing principles, strengths, and future trends.