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Controllable image synthesis with user scribbles has gained huge public interest with the recent advent of text-conditioned latent diffusion models. The user scribbles control the color composition while the text prompt provides control…

Computer Vision and Pattern Recognition · Computer Science 2022-12-01 Jaskirat Singh , Stephen Gould , Liang Zheng

In this paper we describe a learned method of traffic scene generation designed to simulate the output of the perception system of a self-driving car. In our "Scene Diffusion" system, inspired by latent diffusion, we use a novel combination…

Computer Vision and Pattern Recognition · Computer Science 2023-05-31 Ethan Pronovost , Kai Wang , Nick Roy

Fashionable image generation aims to synthesize images of diverse fashion prevalent around the globe, helping fashion designers in real-time visualization by giving them a basic customized structure of how a specific design preference would…

Computer Vision and Pattern Recognition · Computer Science 2023-06-14 Krishna Sri Ipsit Mantri , Nevasini Sasikumar

Diffusion-based text-to-image models have achieved remarkable results in synthesizing diverse images from text prompts and can capture specific artistic styles via style personalization. However, their entangled latent space and lack of…

Computer Vision and Pattern Recognition · Computer Science 2025-08-06 Jaehyun Lee , Wonhark Park , Wonsik Shin , Hyunho Lee , Hyoung Min Na , Nojun Kwak

Latent diffusion models for image generation have crossed a quality threshold which enabled them to achieve mass adoption. Recently, a series of works have made advancements towards replicating this success in the 3D domain, introducing…

Computer Vision and Pattern Recognition · Computer Science 2023-03-29 Anchit Gupta , Wenhan Xiong , Yixin Nie , Ian Jones , Barlas Oğuz

Generative models have advanced significantly in realistic image synthesis, with diffusion models excelling in quality and stability. Recent multi-view diffusion models improve 3D-aware street view generation, but they struggle to produce…

Computer Vision and Pattern Recognition · Computer Science 2026-02-13 Ji Li , Zhiwei Li , Shihao Li , Zhenjiang Yu , Boyang Wang , Haiou Liu

Recent advancements in text-to-image diffusion models have yielded impressive results in generating realistic and diverse images. However, these models still struggle with complex prompts, such as those that involve numeracy and spatial…

Computer Vision and Pattern Recognition · Computer Science 2024-03-05 Long Lian , Boyi Li , Adam Yala , Trevor Darrell

Latent Diffusion Models (LDMs) enable high-quality image synthesis while avoiding excessive compute demands by training a diffusion model in a compressed lower-dimensional latent space. Here, we apply the LDM paradigm to high-resolution…

Computer Vision and Pattern Recognition · Computer Science 2023-12-29 Andreas Blattmann , Robin Rombach , Huan Ling , Tim Dockhorn , Seung Wook Kim , Sanja Fidler , Karsten Kreis

We present Text2Tex, a novel method for generating high-quality textures for 3D meshes from the given text prompts. Our method incorporates inpainting into a pre-trained depth-aware image diffusion model to progressively synthesize high…

Computer Vision and Pattern Recognition · Computer Science 2023-03-22 Dave Zhenyu Chen , Yawar Siddiqui , Hsin-Ying Lee , Sergey Tulyakov , Matthias Nießner

Consistency Models (CMs) have significantly accelerated the sampling process in diffusion models, yielding impressive results in synthesizing high-resolution images. To explore and extend these advancements to point-cloud-based 3D shape…

Computer Vision and Pattern Recognition · Computer Science 2025-12-30 Bi'an Du , Wei Hu , Renjie Liao

Diffusion models have exhibit exceptional performance in text-to-image generation and editing. However, existing methods often face challenges when handling complex text prompts that involve multiple objects with multiple attributes and…

Computer Vision and Pattern Recognition · Computer Science 2024-06-05 Ling Yang , Zhaochen Yu , Chenlin Meng , Minkai Xu , Stefano Ermon , Bin Cui

We introduce a framework for intrinsic latent diffusion models operating directly on the surfaces of 3D shapes, with the goal of synthesizing high-quality textures. Our approach is underpinned by two contributions: field latents, a latent…

Computer Vision and Pattern Recognition · Computer Science 2024-05-30 Thomas W. Mitchel , Carlos Esteves , Ameesh Makadia

Deep learning methods have impacted almost every research field, demonstrating notable successes in medical imaging tasks such as denoising and super-resolution. However, the prerequisite for deep learning is data at scale, but data sharing…

Medical Physics · Physics 2024-02-16 Yongyi Shi , Wenjun Xia , Chuang Niu , Christopher Wiedeman , Ge Wang

Generative AI offers new opportunities for automating urban planning by creating site-specific urban layouts and enabling flexible design exploration. However, existing approaches often struggle to produce realistic and practical designs at…

Computer Vision and Pattern Recognition · Computer Science 2025-05-15 Qingyi Wang , Yuebing Liang , Yunhan Zheng , Kaiyuan Xu , Jinhua Zhao , Shenhao Wang

Recent advancements in layout pattern generation have been dominated by deep generative models. However, relying solely on neural networks for legality guarantees raises concerns in many practical applications. In this paper, we present…

Machine Learning · Computer Science 2025-05-09 Zixiao Wang , Wenqian Zhao , Yunheng Shen , Yang Bai , Guojin Chen , Farzan Farnia , Bei Yu

Diffusion generative models have recently greatly improved the power of text-conditioned image generation. Existing image generation models mainly include text conditional diffusion model and cross-modal guided diffusion model, which are…

Computer Vision and Pattern Recognition · Computer Science 2022-11-04 Wei Li , Xue Xu , Xinyan Xiao , Jiachen Liu , Hu Yang , Guohao Li , Zhanpeng Wang , Zhifan Feng , Qiaoqiao She , Yajuan Lyu , Hua Wu

In this paper, we propose a novel garment-centric outpainting (GCO) framework based on the latent diffusion model (LDM) for fine-grained controllable apparel showcase image generation. The proposed framework aims at customizing a fashion…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Rong Zhang , Jingnan Wang , Zhiwen Zuo , Jianfeng Dong , Wei Li , Chi Wang , Weiwei Xu , Xun Wang

Text-conditioned image generation has made significant progress in recent years with generative adversarial networks and more recently, diffusion models. While diffusion models conditioned on text prompts have produced impressive and…

Computer Vision and Pattern Recognition · Computer Science 2023-05-01 Azade Farshad , Yousef Yeganeh , Yu Chi , Chengzhi Shen , Björn Ommer , Nassir Navab

Generative 3D Painting is among the top productivity boosters in high-resolution 3D asset management and recycling. Ever since text-to-image models became accessible for inference on consumer hardware, the performance of 3D Painting methods…

Computer Vision and Pattern Recognition · Computer Science 2024-06-18 Tianfu Wang , Anton Obukhov , Konrad Schindler

We introduce a diffusion-based framework that performs aligned novel view image and geometry generation via a warping-and-inpainting methodology. Unlike prior methods that require dense posed images or pose-embedded generative models…

Computer Vision and Pattern Recognition · Computer Science 2026-02-09 Min-Seop Kwak , Junho Kim , Sangdoo Yun , Dongyoon Han , Taekyung Kim , Seungryong Kim , Jin-Hwa Kim