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Synthesizing semantic-aware, long-horizon, human-object interaction is critical to simulate realistic human behaviors. In this work, we address the challenging problem of generating synchronized object motion and human motion guided by…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Jiaman Li , Alexander Clegg , Roozbeh Mottaghi , Jiajun Wu , Xavier Puig , C. Karen Liu

Recent advances in text-to-vision generation excel in visual fidelity but struggle with compositional generalization and semantic alignment. Existing datasets are noisy and weakly compositional, limiting models' understanding of complex…

Computer Vision and Pattern Recognition · Computer Science 2026-03-18 Ziqi Gao , Weikai Huang , Jieyu Zhang , Aniruddha Kembhavi , Ranjay Krishna

We present SceneFactor, a diffusion-based approach for large-scale 3D scene generation that enables controllable generation and effortless editing. SceneFactor enables text-guided 3D scene synthesis through our factored diffusion…

Computer Vision and Pattern Recognition · Computer Science 2024-12-04 Alexey Bokhovkin , Quan Meng , Shubham Tulsiani , Angela Dai

We present TeSMo, a method for text-controlled scene-aware motion generation based on denoising diffusion models. Previous text-to-motion methods focus on characters in isolation without considering scenes due to the limited availability of…

Computer Vision and Pattern Recognition · Computer Science 2024-04-17 Hongwei Yi , Justus Thies , Michael J. Black , Xue Bin Peng , Davis Rempe

Recent advancements in diffusion models have greatly improved the quality and diversity of synthesized content. To harness the expressive power of diffusion models, researchers have explored various controllable mechanisms that allow users…

Computer Vision and Pattern Recognition · Computer Science 2023-04-28 Tsai-Shien Chen , Chieh Hubert Lin , Hung-Yu Tseng , Tsung-Yi Lin , Ming-Hsuan Yang

While diffusion models excel at generating high-quality images from text prompts, they struggle with visual consistency when generating image sequences. Existing methods generate each image independently, leading to disjointed narratives -…

Computer Vision and Pattern Recognition · Computer Science 2025-09-24 Guilherme Fernandes , Vasco Ramos , Regev Cohen , Idan Szpektor , João Magalhães

We present CineVerse, a novel framework for the task of cinematic scene composition. Similar to traditional multi-shot generation, our task emphasizes the need for consistency and continuity across frames. However, our task also focuses on…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Quynh Phung , Long Mai , Fabian David Caba Heilbron , Feng Liu , Jia-Bin Huang , Cusuh Ham

Diffusion models emerged as a leading approach in text-to-image generation, producing high-quality images from textual descriptions. However, attempting to achieve detailed control to get a desired image solely through text remains a…

Computer Vision and Pattern Recognition · Computer Science 2026-02-12 Pablo Domingo-Gregorio , Javier Ruiz-Hidalgo

With recent developments in Embodied Artificial Intelligence (EAI) research, there has been a growing demand for high-quality, large-scale interactive scene generation. While prior methods in scene synthesis have prioritized the naturalness…

Computer Vision and Pattern Recognition · Computer Science 2024-07-11 Yandan Yang , Baoxiong Jia , Peiyuan Zhi , Siyuan Huang

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

Designing 3D scenes is currently a creative task that requires significant expertise and effort in using complex 3D design interfaces. This effortful design process starts in stark contrast to the easiness with which people can use language…

Graphics · Computer Science 2017-03-02 Angel X. Chang , Mihail Eric , Manolis Savva , Christopher D. Manning

Automatic image synthesis research has been rapidly growing with deep networks getting more and more expressive. In the last couple of years, we have observed images of digits, indoor scenes, birds, chairs, etc. being automatically…

Computer Vision and Pattern Recognition · Computer Science 2016-12-02 Levent Karacan , Zeynep Akata , Aykut Erdem , Erkut Erdem

Large language models (LLMs) have achieved remarkable success in text-based tasks but often struggle to provide actionable guidance in real-world physical environments. This is because of their inability to recognize their limited…

Computer Vision and Pattern Recognition · Computer Science 2025-03-05 Muhammad Saif Ullah Khan , Muhammad Zeshan Afzal , Didier Stricker

Controllable 3D indoor scene synthesis stands at the forefront of technological progress, offering various applications like gaming, film, and augmented/virtual reality. The capability to stylize and de-couple objects within these scenarios…

Computer Vision and Pattern Recognition · Computer Science 2024-01-25 Yunfan Zhang , Hong Huang , Zhiwei Xiong , Zhiqi Shen , Guosheng Lin , Hao Wang , Nicholas Vun

Integrating motion into static images not only enhances visual expressiveness but also creates a sense of immersion and temporal depth, establishing it as a longstanding and impactful theme in artistic expression. Fluid elements such as…

Graphics · Computer Science 2025-10-21 Hao Jin , Haoran Xie

Despite enormous progress in object detection and classification, the problem of incorporating expected contextual relationships among object instances into modern recognition systems remains a key challenge. In this work we propose…

Computer Vision and Pattern Recognition · Computer Science 2017-01-11 Ehsan Jahangiri , Erdem Yoruk , Rene Vidal , Laurent Younes , Donald Geman

With the rapid development of diffusion models in image generation, the demand for more powerful and flexible controllable frameworks is increasing. Although existing methods can guide generation beyond text prompts, the challenge of…

Computer Vision and Pattern Recognition · Computer Science 2025-07-09 Haoxuan Wang , Jinlong Peng , Qingdong He , Hao Yang , Ying Jin , Jiafu Wu , Xiaobin Hu , Yanjie Pan , Zhenye Gan , Mingmin Chi , Bo Peng , Yabiao Wang

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

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

Designing realistic multi-object scenes requires not only generating images, but also planning spatial layouts that respect semantic relations and physical plausibility. On one hand, while recent advances in diffusion models have enabled…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Zezhong Fan , Xiaohan Li , Luyi Ma , Kai Zhao , Liang Peng , Topojoy Biswas , Evren Korpeoglu , Kaushiki Nag , Kannan Achan
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