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20222026
most citedSANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformers

5 citations · 20 across the 17 of their papers we have counts for

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Showing 2025Show all

9 papers · 1 filter

cs.CV2025

SANA-Video: Efficient Video Generation with Block Linear Diffusion Transformer

Junsong Chen, Yuyang Zhao, Jincheng Yu +17

We introduce SANA-Video, a small diffusion model that can efficiently generate videos up to 720x1280 resolution and minute-length duration. SANA-Video synthesizes high-resolution,…

cs.CV2025

LongLive: Real-time Interactive Long Video Generation

Shuai Yang, Wei Huang, Ruihang Chu +9

We present LongLive, a frame-level autoregressive (AR) framework for real-time and interactive long video generation. Long video generation presents challenges in both efficiency a…

cs.CV2025

DC-VideoGen: Efficient Video Generation with Deep Compression Video Autoencoder

Junyu Chen, Wenkun He, Yuchao Gu +12

We introduce DC-VideoGen, a post-training acceleration framework for efficient video generation. DC-VideoGen can be applied to any pre-trained video diffusion model, improving effi…

cs.CV2025

DC-Gen: Post-Training Diffusion Acceleration with Deeply Compressed Latent Space

Wenkun He, Yuchao Gu, Junyu Chen +11

Existing text-to-image diffusion models excel at generating high-quality images, but face significant efficiency challenges when scaled to high resolutions, like 4K image generatio…

cs.CV2025

Radial Attention: Sparse Attention with Energy Decay for Long Video Generation

Xingyang Li, Muyang Li, Tianle Cai +11

Recent advances in diffusion models have enabled high-quality video generation, but the additional temporal dimension significantly increases computational costs, making training a…

cs.CV2025

Sparse VideoGen2: Accelerate Video Generation with Sparse Attention via Semantic-Aware Permutation

Shuo Yang, Haocheng Xi, Yilong Zhao +10

Diffusion Transformers (DiTs) are essential for video generation but suffer from significant latency due to the quadratic complexity of attention. By computing only critical tokens…

cs.CV2025★ 1 cited

STORM: Token-Efficient Long Video Understanding for Multimodal LLMs

Jindong Jiang, Xiuyu Li, Zhijian Liu +13

Recent advances in video-based multimodal large language models (Video-LLMs) have significantly improved video understanding by processing videos as sequences of image frames. Howe…

cs.CV2025★ 1 cited

Sparse VideoGen: Accelerating Video Diffusion Transformers with Spatial-Temporal Sparsity

Haocheng Xi, Shuo Yang, Yilong Zhao +11

Diffusion Transformers (DiTs) dominate video generation but their high computational cost severely limits real-world applicability, usually requiring tens of minutes to generate a…

cs.CV2025★ 1 cited

SANA 1.5: Efficient Scaling of Training-Time and Inference-Time Compute in Linear Diffusion Transformer

Enze Xie, Junsong Chen, Yuyang Zhao +11

This paper presents SANA-1.5, a linear Diffusion Transformer for efficient scaling in text-to-image generation. Building upon SANA-1.0, we introduce three key innovations: (1) Effi…