activity
20232026
most citedReal-time One-Step Diffusion-based Expressive Portrait Videos Generation

1 citations · 2 across the 9 of their papers we have counts for

collaborators

10 papers

cs.CV2026

SANA-Video 2.0: Hybrid Linear Attention with Attention Residuals for Efficient Video Generation

Junsong Chen, Jincheng Yu, Yitong Li +11

We introduce SANA-Video 2.0, a hybrid video diffusion transformer instantiated at 5B and 14B scales under a unified architecture. Designed to generate high-quality video up to 720p…

cs.CV2026

SyncCache: Exploiting Asymmetric Dynamics for Fast Audio-Driven Portrait Animation

Juncheng Ma, Yuxuan Du, Yanan Sun +8

Diffusion Transformers (DiTs) have significantly advanced audio-driven portrait animation, but their high computational cost leads to substantial inference latency. Although traini…

cs.CV2026

EgoReAct: Egocentric Video-Driven 3D Human Reaction Generation

Libo Zhang, Zekun Li, Tianyu Li +10

Humans exhibit adaptive, context-sensitive responses to egocentric visual input. However, faithfully modeling such reactions from egocentric video remains challenging due to the du…

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

MagicDistillation: Weak-to-Strong Video Distillation for Large-Scale Few-Step Synthesis

Shitong Shao, Hongwei Yi, Hanzhong Guo +5

Recently, open-source video diffusion models (VDMs), such as WanX, Magic141 and HunyuanVideo, have been scaled to over 10 billion parameters. These large-scale VDMs have demonstrat…

cs.CV2025

MagicInfinite: Generating Infinite Talking Videos with Your Words and Voice

Hongwei Yi, Tian Ye, Shitong Shao +10

We present MagicInfinite, a novel diffusion Transformer (DiT) framework that overcomes traditional portrait animation limitations, delivering high-fidelity results across diverse c…

cs.CV2025

Magic 1-For-1: Generating One Minute Video Clips within One Minute

Hongwei Yi, Shitong Shao, Tian Ye +7

In this technical report, we present Magic 1-For-1 (Magic141), an efficient video generation model with optimized memory consumption and inference latency. The key idea is simple:…

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…

cs.CV2024★ 1 cited

Real-time One-Step Diffusion-based Expressive Portrait Videos Generation

Hanzhong Guo, Hongwei Yi, Daquan Zhou +3

Latent diffusion models have made great strides in generating expressive portrait videos with accurate lip-sync and natural motion from a single reference image and audio input. Ho…

cs.CV2023

Factorization Vision Transformer: Modeling Long Range Dependency with Local Window Cost

Haolin Qin, Daquan Zhou, Tingfa Xu +2

Transformers have astounding representational power but typically consume considerable computation which is quadratic with image resolution. The prevailing Swin transformer reduces…