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In this paper, we present DesignDiffusion, a simple yet effective framework for the novel task of synthesizing design images from textual descriptions. A primary challenge lies in generating accurate and style-consistent textual and visual…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Zhendong Wang , Jianmin Bao , Shuyang Gu , Dong Chen , Wengang Zhou , Houqiang Li

The recently developed discrete diffusion models perform extraordinarily well in the text-to-image task, showing significant promise for handling the multi-modality signals. In this work, we harness these traits and present a unified…

Computer Vision and Pattern Recognition · Computer Science 2022-11-29 Minghui Hu , Chuanxia Zheng , Heliang Zheng , Tat-Jen Cham , Chaoyue Wang , Zuopeng Yang , Dacheng Tao , Ponnuthurai N. Suganthan

Diffusion models have gained tremendous success in text-to-image generation, yet still lag behind with visual understanding tasks, an area dominated by autoregressive vision-language models. We propose a large-scale and fully end-to-end…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Zijie Li , Henry Li , Yichun Shi , Amir Barati Farimani , Yuval Kluger , Linjie Yang , Peng Wang

A unified diffusion framework for multi-modal generation and understanding has the transformative potential to achieve seamless and controllable image diffusion and other cross-modal tasks. In this paper, we introduce MMGen, a unified…

Computer Vision and Pattern Recognition · Computer Science 2025-03-27 Jiepeng Wang , Zhaoqing Wang , Hao Pan , Yuan Liu , Dongdong Yu , Changhu Wang , Wenping Wang

Diffusion models currently achieve state-of-the-art performance for both conditional and unconditional image generation. However, so far, image diffusion models do not support tasks required for 3D understanding, such as view-consistent 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-02-22 Titas Anciukevičius , Zexiang Xu , Matthew Fisher , Paul Henderson , Hakan Bilen , Niloy J. Mitra , Paul Guerrero

Large-scale generative models, such as text-to-image diffusion models, have garnered widespread attention across diverse domains due to their creative and high-fidelity image generation. Nonetheless, existing large-scale diffusion models…

Computer Vision and Pattern Recognition · Computer Science 2024-08-28 Younghyun Kim , Geunmin Hwang , Junyu Zhang , Eunbyung Park

Video generation models have made significant progress in generating realistic content, enabling applications in simulation, gaming, and film making. However, current generated videos still contain visual artifacts arising from 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Duolikun Danier , Ge Gao , Steven McDonagh , Changjian Li , Hakan Bilen , Oisin Mac Aodha

Multi-view diffusion models have recently emerged as a powerful paradigm for novel view synthesis, yet the underlying mechanism that enables their view-consistency remains unclear. In this work, we first verify that the attention maps of…

Computer Vision and Pattern Recognition · Computer Science 2025-12-03 Minkyung Kwon , Jinhyeok Choi , Jiho Park , Seonghu Jeon , Jinhyuk Jang , Junyoung Seo , Minseop Kwak , Jin-Hwa Kim , Seungryong Kim

Collecting multi-view driving scenario videos to enhance the performance of 3D visual perception tasks presents significant challenges and incurs substantial costs, making generative models for realistic data an appealing alternative. Yet,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Junpeng Jiang , Gangyi Hong , Miao Zhang , Hengtong Hu , Kun Zhan , Rui Shao , Liqiang Nie

Video composition is the core task of video editing. Although image composition based on diffusion models has been highly successful, it is not straightforward to extend the achievement to video object composition tasks, which not only…

Computer Vision and Pattern Recognition · Computer Science 2024-06-25 Wei Wang , Yaosen Chen , Yuegen Liu , Qi Yuan , Shubin Yang , Yanru Zhang

Despite the success of generating high-quality images given any text prompts by diffusion-based generative models, prior works directly generate the entire images, but cannot provide object-wise manipulation capability. To support wider…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Runhui Huang , Kaixin Cai , Jianhua Han , Xiaodan Liang , Renjing Pei , Guansong Lu , Songcen Xu , Wei Zhang , Hang Xu

Recent advances in diffusion models have achieved remarkable success in isolated computer vision tasks such as text-to-image generation, depth estimation, and optical flow. However, these models are often restricted by a…

Computer Vision and Pattern Recognition · Computer Science 2025-11-12 Yilin Gao , Shuguang Dou , Junzhou Li , Zhiheng Yu , Yin Li , Dongsheng Jiang , Shugong Xu

Novel View Synthesis (NVS), which tries to produce a realistic image at the target view given source view images and their corresponding poses, is a fundamental problem in 3D Vision. As this task is heavily under-constrained, some recent…

Computer Vision and Pattern Recognition · Computer Science 2023-12-15 Shijie Li , Farhad G. Zanjani , Haitam Ben Yahia , Yuki M. Asano , Juergen Gall , Amirhossein Habibian

The task of image-to-multi-view generation refers to generating novel views of an instance from a single image. Recent methods achieve this by extending text-to-image latent diffusion models to multi-view version, which contains an VAE…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Zhenggang Tang , Peiye Zhuang , Chaoyang Wang , Aliaksandr Siarohin , Yash Kant , Alexander Schwing , Sergey Tulyakov , Hsin-Ying Lee

Generating consistent human images with controllable pose and appearance is essential for applications in virtual try on, image editing, and digital human creation. Current methods often suffer from occlusions, garment style drift, and pose…

Computer Vision and Pattern Recognition · Computer Science 2025-12-18 Ziyu Shang , Haoran Liu , Rongchao Zhang , Zhiqian Wei , Tongtong Feng

We present a diffusion-based model for 3D-aware generative novel view synthesis from as few as a single input image. Our model samples from the distribution of possible renderings consistent with the input and, even in the presence of…

Computer Vision and Pattern Recognition · Computer Science 2023-04-06 Eric R. Chan , Koki Nagano , Matthew A. Chan , Alexander W. Bergman , Jeong Joon Park , Axel Levy , Miika Aittala , Shalini De Mello , Tero Karras , Gordon Wetzstein

The goal of image-based virtual try-on is to generate an image of the target person naturally wearing the given clothing. However, existing methods solely focus on the frontal try-on using the frontal clothing. When the views of the…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Haoyu Wang , Zhilu Zhang , Donglin Di , Shiliang Zhang , Wangmeng Zuo

Current image captioning works usually focus on generating descriptions in an autoregressive manner. However, there are limited works that focus on generating descriptions non-autoregressively, which brings more decoding diversity. Inspired…

Computer Vision and Pattern Recognition · Computer Science 2023-05-23 Yufeng He , Zefan Cai , Xu Gan , Baobao Chang

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

For an artist or a graphic designer, the spatial layout of a scene is a critical design choice. However, existing text-to-image diffusion models provide limited support for incorporating spatial information. This paper introduces Composite…

Computer Vision and Pattern Recognition · Computer Science 2023-07-27 Vikram Jamwal , Ramaneswaran S