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Given a style-reference image as the additional image condition, text-to-image diffusion models have demonstrated impressive capabilities in generating images that possess the content of text prompts while adopting the visual style of the…

Computer Vision and Pattern Recognition · Computer Science 2025-02-12 Lin Zhu , Xinbing Wang , Chenghu Zhou , Qinying Gu , Nanyang Ye

In layout-to-image (L2I) synthesis, controlled complex scenes are generated from coarse information like bounding boxes. Such a task is exciting to many downstream applications because the input layouts offer strong guidance to the…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Ruyu Wang , Xuefeng Hou , Sabrina Schmedding , Marco F. Huber

Motion transfer from the driving to the source portrait remains a key challenge in the portrait animation. Current diffusion-based approaches condition only on the driving motion, which fails to capture source-to-driving correspondences and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Yating Xu , Yunqi Miao , Evangelos Ververas , Jiankang Deng , Jifei Song

Reference-based sketch colorization methods have garnered significant attention due to their potential applications in the animation production industry. However, most existing methods are trained with image triplets of sketch, reference,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-10 Dingkun Yan , Xinrui Wang , Yusuke Iwasawa , Yutaka Matsuo , Suguru Saito , Jiaxian Guo

3D scene stylization extends the work of neural style transfer to 3D. A vital challenge in this problem is to maintain the uniformity of the stylized appearance across multiple views. A vast majority of the previous works achieve this by…

Computer Vision and Pattern Recognition · Computer Science 2024-09-09 Abhishek Saroha , Mariia Gladkova , Cecilia Curreli , Dominik Muhle , Tarun Yenamandra , Daniel Cremers

Portrait animation aims to generate photo-realistic videos from a single source image by reenacting the expression and pose from a driving video. While early methods relied on 3D morphable models or feature warping techniques, they often…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Mallikarjun B. R. , Fei Yin , Vikram Voleti , Nikita Drobyshev , Maksim Lapin , Aaryaman Vasishta , Varun Jampani

Video try-on replaces clothing in videos with target garments. Existing methods struggle to generate high-quality and temporally consistent results when handling complex clothing patterns and diverse body poses. We present 3DV-TON, a novel…

Computer Vision and Pattern Recognition · Computer Science 2025-04-25 Min Wei , Chaohui Yu , Jingkai Zhou , Fan Wang

We present Stylos, a single-forward 3D Gaussian framework for 3D style transfer that operates on unposed content, from a single image to a multi-view collection, conditioned on a separate reference style image. Stylos synthesizes a stylized…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Hanzhou Liu , Jia Huang , Mi Lu , Srikanth Saripalli , Peng Jiang

Text-to-3D generation has recently garnered significant attention, fueled by 2D diffusion models trained on billions of image-text pairs. Existing methods primarily rely on score distillation to leverage the 2D diffusion priors to supervise…

Computer Vision and Pattern Recognition · Computer Science 2023-07-27 Chaohui Yu , Qiang Zhou , Jingliang Li , Zhe Zhang , Zhibin Wang , Fan Wang

Text-to-video models have demonstrated impressive capabilities in producing diverse and captivating video content, showcasing a notable advancement in generative AI. However, these models generally lack fine-grained control over motion…

Computer Vision and Pattern Recognition · Computer Science 2024-12-09 Tuna Han Salih Meral , Hidir Yesiltepe , Connor Dunlop , Pinar Yanardag

We present DiffuScene for indoor 3D scene synthesis based on a novel scene configuration denoising diffusion model. It generates 3D instance properties stored in an unordered object set and retrieves the most similar geometry for each…

Computer Vision and Pattern Recognition · Computer Science 2024-03-13 Jiapeng Tang , Yinyu Nie , Lev Markhasin , Angela Dai , Justus Thies , Matthias Nießner

Deep learning models for computer vision often suffer from poor generalization when deployed in real-world settings, especially when trained on synthetic data due to the well-known Sim2Real gap. Despite the growing popularity of style…

Computer Vision and Pattern Recognition · Computer Science 2026-04-08 Dustin Eisenhardt , Timothy Schaumlöffel , Alperen Kantarci , Gemma Roig

We seek to give users precise control over diffusion-based image generation by modeling complex scenes as sequences of layers, which define the desired spatial arrangement and visual attributes of objects in the scene. Collage Diffusion…

Computer Vision and Pattern Recognition · Computer Science 2023-09-01 Vishnu Sarukkai , Linden Li , Arden Ma , Christopher Ré , Kayvon Fatahalian

Recent advancements in 3D scene editing have been propelled by the rapid development of generative models. Existing methods typically utilize generative models to perform text-guided editing on 3D representations, such as 3D Gaussian…

Graphics · Computer Science 2025-05-27 Yansong Qu , Dian Chen , Xinyang Li , Xiaofan Li , Shengchuan Zhang , Liujuan Cao , Rongrong Ji

Recent advancements in 3D editing have highlighted the potential of text-driven methods in real-time, user-friendly AR/VR applications. However, current methods rely on 2D diffusion models without adequately considering multi-view…

Computer Vision and Pattern Recognition · Computer Science 2025-04-21 Dong In Lee , Hyeongcheol Park , Jiyoung Seo , Eunbyung Park , Hyunje Park , Ha Dam Baek , Sangheon Shin , Sangmin Kim , Sangpil Kim

Text-conditioned diffusion models can generate impressive images, but fall short when it comes to fine-grained control. Unlike direct-editing tools like Photoshop, text conditioned models require the artist to perform "prompt engineering,"…

Computer Vision and Pattern Recognition · Computer Science 2024-04-05 Michelle Shu , Charles Herrmann , Richard Strong Bowen , Forrester Cole , Ramin Zabih

Both geometry and texture are fundamental aspects of visual style. Existing style transfer methods, however, primarily focus on texture, almost entirely ignoring geometry. We propose deformable style transfer (DST), an optimization-based…

Computer Vision and Pattern Recognition · Computer Science 2020-07-21 Sunnie S. Y. Kim , Nicholas Kolkin , Jason Salavon , Gregory Shakhnarovich

The artistic style within a painting is the means of expression, which includes not only the painting material, colors, and brushstrokes, but also the high-level attributes including semantic elements, object shapes, etc. Previous arbitrary…

Computer Vision and Pattern Recognition · Computer Science 2023-03-21 Yuxin Zhang , Nisha Huang , Fan Tang , Haibin Huang , Chongyang Ma , Weiming Dong , Changsheng Xu

Text-to-3D, known for its efficient generation methods and expansive creative potential, has garnered significant attention in the AIGC domain. However, the pixel-wise rendering of NeRF and its ray marching light sampling constrain the…

Computer Vision and Pattern Recognition · Computer Science 2024-11-27 Xinhai Li , Huaibin Wang , Kuo-Kun Tseng

Image-based virtual try-on is an increasingly important task for online shopping. It aims to synthesize images of a specific person wearing a specified garment. Diffusion model-based approaches have recently become popular, as they are…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Xu Yang , Changxing Ding , Zhibin Hong , Junhao Huang , Jin Tao , Xiangmin Xu