Papers
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Video Generation Acceleration
Training-Free Efficient Video Generation via Dynamic Token Carving
Published:5/23/2025
Efficient Inference of Video Diffusion ModelsDynamic Token CarvingProgressive Resolution GenerationBlock-Wise Attention MechanismVideo Generation Acceleration
The paper presents Jenga, a trainingfree method for efficient video generation that addresses the computational bottlenecks of Video Diffusion Transformers. Jenga achieves 8.83x speedup while maintaining generation quality, significantly enhancing practical application efficienc
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From Slow Bidirectional to Fast Autoregressive Video Diffusion Models
Published:12/11/2024
Autoregressive Video Diffusion ModelsDiffusion Model DistillationVideo Generation AccelerationDynamic Video GenerationLong-Horizon Video Synthesis
The paper introduces a novel autoregressive video diffusion model that transforms a slow bidirectional model into a fast one using distribution matching distillation. With teacher trajectory initialization and asymmetric distillation, it achieves an 84.27 score on VBenchLong, si
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Sparse VideoGen2: Accelerate Video Generation with Sparse Attention via Semantic-Aware Permutation
Published:5/25/2025
Sparse Attention Video GenerationDiffusion TransformersSemantic-Aware PermutationTraining-Free FrameworkVideo Generation Acceleration
This paper presents SVG2, a trainingfree framework that enhances critical token identification accuracy through semanticaware permutation, reducing computation waste and addressing efficiency bottlenecks in sparse attention for video generation, achieving up to 2.30x accelerati
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