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We design a system that learns how to edit visual programs. Our edit network consumes a complete input program and a visual target. From this input, we task our network with predicting a local edit operation that could be applied to the…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 R. Kenny Jones , Renhao Zhang , Aditya Ganeshan , Daniel Ritchie

With the recent fast development of generative models, instruction-based image editing has shown great potential in generating high-quality images. However, the quality of editing highly depends on carefully designed instructions, placing…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Mingde Yao , Zhiyuan You , King-Man Tam , Menglu Wang , Tianfan Xue

Structure-guided image completion aims to inpaint a local region of an image according to an input guidance map from users. While such a task enables many practical applications for interactive editing, existing methods often struggle to…

Computer Vision and Pattern Recognition · Computer Science 2024-04-25 Haitian Zheng , Zhe Lin , Jingwan Lu , Scott Cohen , Eli Shechtman , Connelly Barnes , Jianming Zhang , Qing Liu , Yuqian Zhou , Sohrab Amirghodsi , Jiebo Luo

Recent advancements in instruction-following models have made user interactions with models more user-friendly and efficient, broadening their applicability. In graphic design, non-professional users often struggle to create visually…

Computer Vision and Pattern Recognition · Computer Science 2024-04-24 Wanrong Zhu , Jennifer Healey , Ruiyi Zhang , William Yang Wang , Tong Sun

Instruction-guided generative models, especially those using text-to-image (T2I) and text-to-video (T2V) diffusion frameworks, have advanced the field of content editing in recent years. To extend these capabilities to 4D scene, we…

Computer Vision and Pattern Recognition · Computer Science 2025-04-02 Hasan Iqbal , Nazmul Karim , Umar Khalid , Azib Farooq , Zichun Zhong , Chen Chen , Jing Hua

Scientific illustrations demand both high information density and post-editability. However, current generative models have two major limitations: Frist, image generation models output rasterized images lacking semantic structure, making it…

Computer Vision and Pattern Recognition · Computer Science 2025-11-03 Jianwen Sun , Fanrui Zhang , Yukang Feng , Chuanhao Li , Zizhen Li , Jiaxin Ai , Yifan Chang , Yu Dai , Kaipeng Zhang

Image spatial editing performs geometry-driven transformations, allowing precise control over object layout and camera viewpoints. Current models are insufficient for fine-grained spatial manipulations, motivating a dedicated assessment…

Computer Vision and Pattern Recognition · Computer Science 2026-04-09 Yicheng Xiao , Wenhu Zhang , Lin Song , Yukang Chen , Wenbo Li , Nan Jiang , Tianhe Ren , Haokun Lin , Wei Huang , Haoyang Huang , Xiu Li , Nan Duan , Xiaojuan Qi

The exponential growth of scientific literature in PDF format necessitates advanced tools for efficient and accurate document understanding, summarization, and content optimization. Traditional methods fall short in handling complex layouts…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Kun Qian , Wenjie Li , Tianyu Sun , Wenhong Wang , Wenhan Luo

Generative models, such as diffusion and autoregressive approaches, have demonstrated impressive capabilities in editing natural images. However, applying these tools to scientific charts rests on a flawed assumption: a chart is not merely…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Shawn Li , Ryan Rossi , Sungchul Kim , Sunav Choudhary , Franck Dernoncourt , Puneet Mathur , Zhengzhong Tu , Yue Zhao

Graphic design plays a crucial role in both commercial and personal contexts, yet creating high-quality, editable, and aesthetically pleasing graphic compositions remains a time-consuming and skill-intensive task, especially for beginners.…

Computer Vision and Pattern Recognition · Computer Science 2025-06-13 Zhao Zhang , Yutao Cheng , Dexiang Hong , Maoke Yang , Gonglei Shi , Lei Ma , Hui Zhang , Jie Shao , Xinglong Wu

Incorporating human feedback has been shown to be crucial to align text generated by large language models to human preferences. We hypothesize that state-of-the-art instructional image editing models, where outputs are generated based on…

Computer Vision and Pattern Recognition · Computer Science 2024-03-28 Shu Zhang , Xinyi Yang , Yihao Feng , Can Qin , Chia-Chih Chen , Ning Yu , Zeyuan Chen , Huan Wang , Silvio Savarese , Stefano Ermon , Caiming Xiong , Ran Xu

Semantic segmentation in real-world applications often requires not only accurate masks but also strict adherence to textual labeling guidelines. These guidelines are typically complex and long, and both human and automated labeling often…

Computer Vision and Pattern Recognition · Computer Science 2025-12-17 Vanshika Vats , Ashwani Rathee , James Davis

Building on the success of text-to-image diffusion models (DPMs), image editing is an important application to enable human interaction with AI-generated content. Among various editing methods, editing within the prompt space gains more…

Computer Vision and Pattern Recognition · Computer Science 2025-01-28 Aosong Feng , Weikang Qiu , Jinbin Bai , Xiao Zhang , Zhen Dong , Kaicheng Zhou , Rex Ying , Leandros Tassiulas

Diffusion models have attained remarkable success in the domains of image generation and editing. It is widely recognized that employing larger inversion and denoising steps in diffusion model leads to improved image reconstruction quality.…

Computer Vision and Pattern Recognition · Computer Science 2024-01-05 Chen Hou , Guoqiang Wei , Zhibo Chen

The narrative quality of a video fundamentally determines its perceptual value. Although existing video generation methods can produce visually appealing content, they predominantly rely on sparse conditioning signals such as text prompts…

Computer Vision and Pattern Recognition · Computer Science 2026-05-28 Zhida Zhang , Jie Ma , Zhan Peng , Haoxue Wu , Yang Han , Jun Liang , Jie Cao , Jing Li

Visual prediction has emerged as a promising paradigm for embodied control, where future observations are generated and then translated into actions. However, dense video generation is computationally expensive and often unnecessary for…

Computer Vision and Pattern Recognition · Computer Science 2026-05-20 Yiren Song , Yihan Wang , Xiyao Deng , Zhuoran Yan , Mike Zheng Shou

Text-driven 3D editing seeks to modify 3D scenes according to textual descriptions, and most existing approaches tackle this by adapting pre-trained 2D image editors to multi-view inputs. However, without explicit control over multi-view…

Computer Vision and Pattern Recognition · Computer Science 2026-02-20 Zhe Zhu , Honghua Chen , Peng Li , Mingqiang Wei

Graphic design forms the cornerstone of modern visual communication, serving as a vital medium for promoting cultural and commercial events. Recent advances have explored automating this process using Large Multimodal Models (LMMs), yet…

Computer Vision and Pattern Recognition · Computer Science 2025-12-04 Jiazhe Wei , Ken Li , Tianyu Lao , Haofan Wang , Liang Wang , Caifeng Shan , Chenyang Si

The paper presents an algorithm, called Self-Morphing Adaptive Replanning Tree (SMART), that facilitates fast replanning in dynamic environments. SMART performs risk based tree-pruning if the current path is obstructed by nearby moving…

Robotics · Computer Science 2023-09-22 Zongyuan Shen , James P. Wilson , Shalabh Gupta , Ryan Harvey

We introduce PhotoDoodle, a novel image editing framework designed to facilitate photo doodling by enabling artists to overlay decorative elements onto photographs. Photo doodling is challenging because the inserted elements must appear…

Computer Vision and Pattern Recognition · Computer Science 2025-02-25 Shijie Huang , Yiren Song , Yuxuan Zhang , Hailong Guo , Xueyin Wang , Mike Zheng Shou , Jiaming Liu