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We propose a diffusion-based approach for Text-to-Image (T2I) generation with consistent and interactive 3D layout control and editing. While prior methods improve spatial adherence using 2D cues or iterative copy-warp-paste strategies,…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Andrea Rigo , Luca Stornaiuolo , Weijie Wang , Mauro Martino , Bruno Lepri , Nicu Sebe

Sketch-guided image editing aims to achieve local fine-tuning of the image based on the sketch information provided by the user, while maintaining the original status of the unedited areas. Due to the high cost of acquiring human sketches,…

Computer Vision and Pattern Recognition · Computer Science 2023-11-15 Weihang Mao , Bo Han , Zihao Wang

The pose-guided person image generation task requires synthesizing photorealistic images of humans in arbitrary poses. The existing approaches use generative adversarial networks that do not necessarily maintain realistic textures or need…

Computer Vision and Pattern Recognition · Computer Science 2023-03-02 Ankan Kumar Bhunia , Salman Khan , Hisham Cholakkal , Rao Muhammad Anwer , Jorma Laaksonen , Mubarak Shah , Fahad Shahbaz Khan

Recent advances in text-to-image diffusion models have substantially improved the quality of image customization, enabling the synthesis of highly realistic images. Despite this progress, achieving fast and efficient personalization remains…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Aniket Roy , Maitreya Suin , Rama Chellappa

Dataset bias is a significant challenge in machine learning, where specific attributes, such as texture or color of the images are unintentionally learned resulting in detrimental performance. To address this, previous efforts have focused…

Computer Vision and Pattern Recognition · Computer Science 2024-06-11 Donggeun Ko , Sangwoo Jo , Dongjun Lee , Namjun Park , Jaekwang Kim

Task planning for embodied AI has been one of the most challenging problems where the community does not meet a consensus in terms of formulation. In this paper, we aim to tackle this problem with a unified framework consisting of an…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Cheng-Fu Yang , Haoyang Xu , Te-Lin Wu , Xiaofeng Gao , Kai-Wei Chang , Feng Gao

Generating natural hand-object interactions in 3D is challenging as the resulting hand and object motions are expected to be physically plausible and semantically meaningful. Furthermore, generalization to unseen objects is hindered by the…

Computer Vision and Pattern Recognition · Computer Science 2024-12-24 Sammy Christen , Shreyas Hampali , Fadime Sener , Edoardo Remelli , Tomas Hodan , Eric Sauser , Shugao Ma , Bugra Tekin

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

Subject-driven image inpainting has recently gained prominence in image editing with the rapid advancement of diffusion models. Beyond image guidance, recent studies have explored incorporating text guidance to achieve identity-preserved…

Computer Vision and Pattern Recognition · Computer Science 2025-09-25 Yicheng Yang , Pengxiang Li , Lu Zhang , Liqian Ma , Ping Hu , Siyu Du , Yunzhi Zhuge , Xu Jia , Huchuan Lu

Generative image editing has recently witnessed extremely fast-paced growth. Some works use high-level conditioning such as text, while others use low-level conditioning. Nevertheless, most of them lack fine-grained control over the…

Computer Vision and Pattern Recognition · Computer Science 2024-04-10 Vidit Goel , Elia Peruzzo , Yifan Jiang , Dejia Xu , Xingqian Xu , Nicu Sebe , Trevor Darrell , Zhangyang Wang , Humphrey Shi

Modern Text-to-Image (T2I) Diffusion models have revolutionized image editing by enabling the generation of high-quality photorealistic images. While the de facto method for performing edits with T2I models is through text instructions,…

Computer Vision and Pattern Recognition · Computer Science 2024-11-07 Ashutosh Srivastava , Tarun Ram Menta , Abhinav Java , Avadhoot Jadhav , Silky Singh , Surgan Jandial , Balaji Krishnamurthy

Text-to-image models (T2I) such as StableDiffusion have been used to generate high quality images of people. However, due to the random nature of the generation process, the person has a different appearance e.g. pose, face, and clothing,…

Computer Vision and Pattern Recognition · Computer Science 2023-12-19 Soon Yau Cheong , Armin Mustafa , Andrew Gilbert

Image-to-image translation (I2I), and particularly its subfield of appearance transfer, which seeks to alter the visual appearance between images while maintaining structural coherence, presents formidable challenges. Despite significant…

Computer Vision and Pattern Recognition · Computer Science 2023-11-29 Yuteng Ye , Guanwen Li , Hang Zhou , Cai Jiale , Junqing Yu , Yawei Luo , Zikai Song , Qilong Xing , Youjia Zhang , Wei Yang

Recently, several point-based image editing methods (e.g., DragDiffusion, FreeDrag, DragNoise) have emerged, yielding precise and high-quality results based on user instructions. However, these methods often make insufficient use of…

Computer Vision and Pattern Recognition · Computer Science 2024-12-04 DuoSheng Chen , Binghui Chen , Yifeng Geng , Liefeng Bo

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

As recent advances in large-scale Text-to-Image (T2I) diffusion models have yielded remarkable high-quality image generation, diverse downstream Image-to-Image (I2I) applications have emerged. Despite the impressive results achieved by…

Computer Vision and Pattern Recognition · Computer Science 2024-10-11 Geonung Kim , Beomsu Kim , Eunhyeok Park , Sunghyun Cho

We introduce DialogPaint, a novel framework that bridges conversational interactions with image editing, enabling users to modify images through natural dialogue. By integrating a dialogue model with the Stable Diffusion image…

Computer Vision and Pattern Recognition · Computer Science 2023-10-19 Jingxuan Wei , Shiyu Wu , Xin Jiang , Yequan Wang

In this work, we address a challenge in video inpainting: reconstructing occluded regions in dynamic, real-world scenarios. Motivated by the need for continuous human motion monitoring in healthcare settings, where facial features are…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Zheyan Zhang , Diego Klabjan , Renee CB Manworren

While 2D diffusion models have achieved remarkable success in identity-preserving personalization, extending this capability to 3D assets remains a significant challenge due to the complexities of multi-view consistency and spatial control.…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Jinxin Ai , Matthias Nießner , Ziya Erkoç

Generative text-to-image models, such as Stable Diffusion, have demonstrated a remarkable ability to generate diverse, high-quality images. However, they are surprisingly inept when it comes to rendering human hands, which are often…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Zhenyue Qin , Yiqun Zhang , Yang Liu , Dylan Campbell
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