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Generating 3D visual scenes is at the forefront of visual generative AI, but current 3D generation techniques struggle with generating scenes with multiple high-resolution objects. Here we introduce Lay-A-Scene, which solves the task of…

Computer Vision and Pattern Recognition · Computer Science 2024-06-05 Ohad Rahamim , Hilit Segev , Idan Achituve , Yuval Atzmon , Yoni Kasten , Gal Chechik

Compositionality is a critical capability in Text-to-Image (T2I) models, as it reflects their ability to understand and combine multiple concepts from text descriptions. Existing evaluations of compositional capability rely heavily on…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Xindi Wu , Dingli Yu , Yangsibo Huang , Olga Russakovsky , Sanjeev Arora

Recent advances in text-to-image (T2I) generation have shown remarkable success in producing high-quality images from text. However, existing T2I models show decayed performance in compositional image generation involving multiple objects…

Computer Vision and Pattern Recognition · Computer Science 2024-12-16 Zejian Li , Chenye Meng , Yize Li , Ling Yang , Shengyuan Zhang , Jiarui Ma , Jiayi Li , Guang Yang , Changyuan Yang , Zhiyuan Yang , Jinxiong Chang , Lingyun Sun

Despite significant recent progress on generative models, controlled generation of images depicting multiple and complex object layouts is still a difficult problem. Among the core challenges are the diversity of appearance a given object…

Computer Vision and Pattern Recognition · Computer Science 2019-10-16 Bo Zhao , Lili Meng , Weidong Yin , Leonid Sigal

Object compositing based on 2D images is a challenging problem since it typically involves multiple processing stages such as color harmonization, geometry correction and shadow generation to generate realistic results. Furthermore,…

Computer Vision and Pattern Recognition · Computer Science 2022-12-06 Yizhi Song , Zhifei Zhang , Zhe Lin , Scott Cohen , Brian Price , Jianming Zhang , Soo Ye Kim , Daniel Aliaga

Recent advancements in diffusion models for 2D and 3D content creation have sparked a surge of interest in generating 4D content. However, the scarcity of 3D scene datasets constrains current methodologies to primarily object-centric…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Dejia Xu , Hanwen Liang , Neel P. Bhatt , Hezhen Hu , Hanxue Liang , Konstantinos N. Plataniotis , Zhangyang Wang

Recent breakthroughs in text-to-image diffusion models have significantly advanced the generation of high-fidelity, photo-realistic images from textual descriptions. Yet, these models often struggle with interpreting spatial arrangements…

Computer Vision and Pattern Recognition · Computer Science 2024-07-19 Jiaqi Liu , Tao Huang , Chang Xu

Image compositing is a method used to generate realistic yet fake imagery by inserting contents from one image to another. Previous work in compositing has focused on improving appearance compatibility of a user selected foreground segment…

Graphics · Computer Science 2017-12-05 Fuwen Tan , Crispin Bernier , Benjamin Cohen , Vicente Ordonez , Connelly Barnes

Recent advancements in personalizing text-to-image (T2I) diffusion models have shown the capability to generate images based on personalized visual concepts using a limited number of user-provided examples. However, these models often…

Computer Vision and Pattern Recognition · Computer Science 2024-02-20 Yan Hong , Jianfu Zhang

Text-to-Image (T2I) generation has long been an open problem, with compositional synthesis remaining particularly challenging. This task requires accurate rendering of complex scenes containing multiple objects that exhibit diverse…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Shijian Wang , Runhao Fu , Siyi Zhao , Qingqin Zhan , Xingjian Wang , Jiarui Jin , Yuan Lu , Hanqian Wu , Cunjian Chen

Despite recent advances in text-to-image (T2I) models, they often fail to faithfully render all elements of complex prompts, frequently omitting or misrepresenting specific objects and attributes. Test-time optimization has emerged as a…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Mohammad Hossein Sameti , Amir M. Mansourian , Arash Marioriyad , Soheil Fadaee Oshyani , Mohammad Hossein Rohban , Mahdieh Soleymani Baghshah

Image composition and generation are processes where the artists need control over various parts of the generated images. However, the current state-of-the-art generation models, like Stable Diffusion, cannot handle fine-grained part-level…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Harsh Rangwani , Aishwarya Agarwal , Kuldeep Kulkarni , R. Venkatesh Babu , Srikrishna Karanam

A layout to image (L2I) generation model aims to generate a complicated image containing multiple objects (things) against natural background (stuff), conditioned on a given layout. Built upon the recent advances in generative adversarial…

Computer Vision and Pattern Recognition · Computer Science 2021-03-23 Sen He , Wentong Liao , Michael Ying Yang , Yongxin Yang , Yi-Zhe Song , Bodo Rosenhahn , Tao Xiang

Existing generative approaches for guided image synthesis of multi-object scenes typically rely on 2D controls in the image or text space. As a result, these methods struggle to maintain and respect consistent three-dimensional geometric…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Léopold Maillard , Tom Durand , Adrien Ramanana Rahary , Maks Ovsjanikov

We introduce a method for composing object-level visual prompts within a text-to-image diffusion model. Our approach addresses the task of generating semantically coherent compositions across diverse scenes and styles, similar to the…

Computer Vision and Pattern Recognition · Computer Science 2025-01-03 Gaurav Parmar , Or Patashnik , Kuan-Chieh Wang , Daniil Ostashev , Srinivasa Narasimhan , Jun-Yan Zhu , Daniel Cohen-Or , Kfir Aberman

We introduce the first generative model capable of simultaneous multi-object compositing, guided by both text and layout. Our model allows for the addition of multiple objects within a scene, capturing a range of interactions from simple…

Computer Vision and Pattern Recognition · Computer Science 2025-02-10 Gemma Canet Tarrés , Zhe Lin , Zhifei Zhang , He Zhang , Andrew Gilbert , John Collomosse , Soo Ye Kim

Text-to-image (T2I) generation has seen significant progress with diffusion models, enabling generation of photo-realistic images from text prompts. Despite this progress, existing methods still face challenges in following complex text…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Ashish Goswami , Satyam Kumar Modi , Santhosh Rishi Deshineni , Harman Singh , Prathosh A. P , Parag Singla

Large-scale diffusion models have achieved state-of-the-art results on text-to-image synthesis (T2I) tasks. Despite their ability to generate high-quality yet creative images, we observe that attribution-binding and compositional…

Computer Vision and Pattern Recognition · Computer Science 2023-03-02 Weixi Feng , Xuehai He , Tsu-Jui Fu , Varun Jampani , Arjun Akula , Pradyumna Narayana , Sugato Basu , Xin Eric Wang , William Yang Wang

In the text-to-image generation field, recent remarkable progress in Stable Diffusion makes it possible to generate rich kinds of novel photorealistic images. However, current models still face misalignment issues (e.g., problematic spatial…

Computer Vision and Pattern Recognition · Computer Science 2023-08-15 Leigang Qu , Shengqiong Wu , Hao Fei , Liqiang Nie , Tat-Seng Chua

Although recent text-to-image generative models have achieved impressive performance, they still often struggle with capturing the compositional complexities of prompts including attribute binding, and spatial relationships between…

Computer Vision and Pattern Recognition · Computer Science 2025-03-17 Seyed Mohammad Hadi Hosseini , Amir Mohammad Izadi , Ali Abdollahi , Armin Saghafian , Mahdieh Soleymani Baghshah