GTA generates 3D worlds from single images via a two-stage video diffusion process that prioritizes geometry before appearance to improve structural consistency.
A survey on long video generation: Challenges, methods, and prospects
4 Pith papers cite this work. Polarity classification is still indexing.
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2026 4verdicts
UNVERDICTED 4roles
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RhymeFlow is a training-free acceleration framework that decouples denoising trajectories across video frames by dense processing of semantic keyframes and asynchronous skipping for non-keyframes, augmented by a latent trajectory projection module to maintain consistency.
DrawVideo is a sketch-guided framework that decomposes long videos into controllable shots using keyframe sketches, appearance prompts, and motion prompts, supported by a new SketchLongVideo dataset.
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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GTA: Advancing Image-to-3D World Generation via Geometry Then Appearance Video Diffusion
GTA generates 3D worlds from single images via a two-stage video diffusion process that prioritizes geometry before appearance to improve structural consistency.
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RhymeFlow: Training-Free Acceleration for Video Generation with Asynchronous Denoising Flow Scheduling
RhymeFlow is a training-free acceleration framework that decouples denoising trajectories across video frames by dense processing of semantic keyframes and asynchronous skipping for non-keyframes, augmented by a latent trajectory projection module to maintain consistency.
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DrawVideo: Generating Long Video from Storyboard Keyframe Sketches
DrawVideo is a sketch-guided framework that decomposes long videos into controllable shots using keyframe sketches, appearance prompts, and motion prompts, supported by a new SketchLongVideo dataset.
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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.