papers

Publications (11)

cs.CV2024

Dimba: Transformer-Mamba Diffusion Models

Zhengcong Fei, Mingyuan Fan, Changqian Yu +3

This paper unveils Dimba, a new text-to-image diffusion model that employs a distinctive hybrid architecture combining Transformer and Mamba elements. Specifically, Dimba sequentia…

cs.CV2025

SkyReels-V2: Infinite-length Film Generative Model

Guibin Chen, Dixuan Lin, Jiangping Yang +22

Recent advances in video generation have been driven by diffusion models and autoregressive frameworks, yet critical challenges persist in harmonizing prompt adherence, visual qual…

cs.CV2024

Scaling Diffusion Transformers to 16 Billion Parameters

Zhengcong Fei, Mingyuan Fan, Changqian Yu +2

In this paper, we present DiT-MoE, a sparse version of the diffusion Transformer, that is scalable and competitive with dense networks while exhibiting highly optimized inference.…

cs.CV2025

Ingredients: Blending Custom Photos with Video Diffusion Transformers

Zhengcong Fei, Debang Li, Di Qiu +2

This paper presents a powerful framework to customize video creations by incorporating multiple specific identity (ID) photos, with video diffusion Transformers, referred to as Ing…

cs.CV2018

A2-RL: Aesthetics Aware Reinforcement Learning for Image Cropping

Debang Li, Huikai Wu, Junge Zhang +1

Image cropping aims at improving the aesthetic quality of images by adjusting their composition. Most weakly supervised cropping methods (without bounding box supervision) rely on…

cs.CV2026

SkyReels-V4: Multi-modal Video-Audio Generation, Inpainting and Editing model

Guibin Chen, Dixuan Lin, Jiangping Yang +48

SkyReels V4 is a unified multi modal video foundation model for joint video audio generation, inpainting, and editing. The model adopts a dual stream Multimodal Diffusion Transform…

cs.CV2026

SkyReels-V3 Technique Report

Debang Li, Zhengcong Fei, Tuanhui Li +19

Video generation serves as a cornerstone for building world models, where multimodal contextual inference stands as the defining test of capability. In this end, we present SkyReel…

cs.CV2025

SkyReels-A2: Compose Anything in Video Diffusion Transformers

Zhengcong Fei, Debang Li, Di Qiu +8

This paper presents SkyReels-A2, a controllable video generation framework capable of assembling arbitrary visual elements (e.g., characters, objects, backgrounds) into synthesized…

cs.CV2024

Diffusion-RWKV: Scaling RWKV-Like Architectures for Diffusion Models

Zhengcong Fei, Mingyuan Fan, Changqian Yu +2

Transformers have catalyzed advancements in computer vision and natural language processing (NLP) fields. However, substantial computational complexity poses limitations for their…

cs.CV2025

Video Diffusion Transformers are In-Context Learners

Zhengcong Fei, Di Qiu, Debang Li +2

This paper investigates a solution for enabling in-context capabilities of video diffusion transformers, with minimal tuning required for activation. Specifically, we propose a sim…

cs.CV2025

SkyReels-Audio: Omni Audio-Conditioned Talking Portraits in Video Diffusion Transformers

Zhengcong Fei, Hao Jiang, Di Qiu +8

The generation and editing of audio-conditioned talking portraits guided by multimodal inputs, including text, images, and videos, remains under explored. In this paper, we present…