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Text-to-video generative models have made remarkable advancements in recent years. However, generating RGBA videos with alpha channels for transparency and visual effects remains a significant challenge due to the scarcity of suitable…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Xuewei Chen , Zhimin Chen , Yiren Song

We introduce the first method, to the best of our knowledge, for adapting image-to-video models to layer-aware text (glyph) animation, a capability critical for practical dynamic visual design. Existing approaches predominantly handle the…

Computer Vision and Pattern Recognition · Computer Science 2026-03-20 Fei Zhang , Zijian Zhou , Bohao Tang , Sen He , Hang Li , Zhe Wang , Soubhik Sanyal , Pengfei Liu , Viktar Atliha , Tao Xiang , Frost Xu , Semih Gunel

Generating RGB-A videos, which include alpha channels for transparency, has wide applications. However, current methods often suffer from low quality due to confusion between RGB and alpha. In this paper, we address this problem by learning…

Computer Vision and Pattern Recognition · Computer Science 2025-12-17 Haotian Dong , Wenjing Wang , Chen Li , Jing Lyu , Di Lin

RGBA images, with the additional alpha channel, are crucial for any application that needs blending, masking, or transparency effects, making them more versatile than standard RGB images. Nevertheless, existing image inpainting methods are…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Yuekun Dai , Haitian Li , Shangchen Zhou , Chen Change Loy

Recent advances in diffusion models have greatly improved image generation and editing, yet generating or reconstructing layered PSD files with transparent alpha channels remains highly challenging. We propose OmniPSD, a unified diffusion…

Computer Vision and Pattern Recognition · Computer Science 2025-12-11 Cheng Liu , Yiren Song , Haofan Wang , Mike Zheng Shou

Diffusion models have exhibited promising progress in video generation. However, they often struggle to retain consistent details within local regions across frames. One underlying cause is that traditional diffusion models approximate…

Computer Vision and Pattern Recognition · Computer Science 2024-05-03 Yupu Yao , Shangqi Deng , Zihan Cao , Harry Zhang , Liang-Jian Deng

The most advanced text-to-image (T2I) models require significant training costs (e.g., millions of GPU hours), seriously hindering the fundamental innovation for the AIGC community while increasing CO2 emissions. This paper introduces…

Computer Vision and Pattern Recognition · Computer Science 2024-01-01 Junsong Chen , Jincheng Yu , Chongjian Ge , Lewei Yao , Enze Xie , Yue Wu , Zhongdao Wang , James Kwok , Ping Luo , Huchuan Lu , Zhenguo Li

Recent advances in latent diffusion models have achieved remarkable results in high-fidelity RGB image synthesis by leveraging pretrained VAEs to compress and reconstruct pixel data at low computational cost. However, the generation of…

Computer Vision and Pattern Recognition · Computer Science 2025-07-15 Zile Wang , Hao Yu , Jiabo Zhan , Chun Yuan

Transparency-aware generation requires modeling not only RGB appearance but also alpha-based opacity and cross-layer composition, which are essential for tasks such as image matting, object removal, layer decomposition, and multi-layer…

Computer Vision and Pattern Recognition · Computer Science 2026-04-29 Hao Yu , Jinglin Wang , Jiabo Zhan , Rui Chen , Zile Wang , Huaisong Zhang , Hongyu Li , Xinrui Chen , Yongxian Wei , Chun Yuan

We present MagicMirror, a framework for generating identity-preserved videos with cinematic-level quality and dynamic motion. While recent advances in video diffusion models have shown impressive capabilities in text-to-video generation,…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Yuechen Zhang , Yaoyang Liu , Bin Xia , Bohao Peng , Zexin Yan , Eric Lo , Jiaya Jia

Transparent image layer generation plays a significant role in digital art and design workflows. Existing methods typically decompose transparent layers from a single RGB image using a set of tools or generate multiple transparent layers…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Dingbang Huang , Wenbo Li , Yifei Zhao , Xinyu Pan , Chun Wang , Yanhong Zeng , Bo Dai

Text-to-image diffusion generative models can generate high quality images at the cost of tedious prompt engineering. Controllability can be improved by introducing layout conditioning, however existing methods lack layout editing ability…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Alessandro Fontanella , Petru-Daniel Tudosiu , Yongxin Yang , Shifeng Zhang , Sarah Parisot

Recent advances in the diffusion models have significantly improved text-to-image generation. However, generating videos from text is a more challenging task than generating images from text, due to the much larger dataset and higher…

Computer Vision and Pattern Recognition · Computer Science 2024-12-31 Taegyeong Lee , Soyeong Kwon , Taehwan Kim

Recent developments in Video Diffusion Models (VDMs) have demonstrated remarkable capability to generate high-quality video content. Nonetheless, the potential of VDMs for creating transparent videos remains largely uncharted. In this…

Graphics · Computer Science 2025-03-04 Menghao Li , Zhenghao Zhang , Junchao Liao , Long Qin , Weizhi Wang

Large-scale diffusion models have achieved remarkable success in generating high-quality images from textual descriptions, gaining popularity across various applications. However, the generation of layered content, such as transparent…

Computer Vision and Pattern Recognition · Computer Science 2024-12-06 Yusuf Dalva , Yijun Li , Qing Liu , Nanxuan Zhao , Jianming Zhang , Zhe Lin , Pinar Yanardag

Video generation has achieved remarkable progress with the introduction of diffusion models, which have significantly improved the quality of generated videos. However, recent research has primarily focused on scaling up model training,…

Computer Vision and Pattern Recognition · Computer Science 2025-01-16 Chenyang Si , Weichen Fan , Zhengyao Lv , Ziqi Huang , Yu Qiao , Ziwei Liu

Text-to-video generation has advanced rapidly, but existing methods typically output only the final composited video and lack editable layered representations, limiting their use in professional workflows. We propose \textbf{LayerT2V}, a…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Guangzhao Li , Kangrui Cen , Baixuan Zhao , Yi Xin , Siqi Luo , Guangtao Zhai , Lei Zhang , Xiaohong Liu

Text-to-video (T2V) generation technology holds potential to transform multiple domains such as education, marketing, entertainment, and assistive technologies for individuals with visual or reading comprehension challenges, by creating…

Graphics · Computer Science 2025-10-07 Nilay Kumar , Priyansh Bhandari , G. Maragatham

Vector graphics, known for their scalability and user-friendliness, provide a unique approach to visual content compared to traditional pixel-based images. Animation of these graphics, driven by the motion of their elements, offers enhanced…

Computer Vision and Pattern Recognition · Computer Science 2025-09-10 Wenshuo Gao , Xicheng Lan , Luyao Zhang , Shuai Yang

Designs and artworks are ubiquitous across various creative fields, requiring graphic design skills and dedicated software to create compositions that include many graphical elements, such as logos, icons, symbols, and art scenes, which are…

Computer Vision and Pattern Recognition · Computer Science 2024-08-28 Fabio Quattrini , Vittorio Pippi , Silvia Cascianelli , Rita Cucchiara
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