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The effective communication of procedural knowledge remains a significant challenge in natural language processing (NLP), as purely textual instructions often fail to convey complex physical actions and spatial relationships. We address…

Computation and Language · Computer Science 2025-05-23 Jing Bi , Pinxin Liu , Ali Vosoughi , Jiarui Wu , Jinxi He , Chenliang Xu

We focus on the foundational task of Scene Staging: given a reference scene image and a text condition specifying an actor category to be generated in the scene and its spatial relation to the scene, the goal is to synthesize an output…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Cong Xie , Che Wang , Yan Zhang , Ruiqi Yu , Han Zou , Zheng Pan , Zhenpeng Zhan

We introduce the new task of generating Illustrated Instructions, i.e., visual instructions customized to a user's needs. We identify desiderata unique to this task, and formalize it through a suite of automatic and human evaluation…

Computer Vision and Pattern Recognition · Computer Science 2024-04-16 Sachit Menon , Ishan Misra , Rohit Girdhar

Generating video stories from text prompts is a complex task. In addition to having high visual quality, videos need to realistically adhere to a sequence of text prompts whilst being consistent throughout the frames. Creating a benchmark…

The performance of computer vision models in certain real-world applications (e.g., rare wildlife observation) is limited by the small number of available images. Expanding datasets using pre-trained generative models is an effective way to…

Computer Vision and Pattern Recognition · Computer Science 2024-12-25 Changjian Chen , Fei Lv , Yalong Guan , Pengcheng Wang , Shengjie Yu , Yifan Zhang , Zhuo Tang

We propose a high-quality 3D-to-3D conversion method, Instruct 3D-to-3D. Our method is designed for a novel task, which is to convert a given 3D scene to another scene according to text instructions. Instruct 3D-to-3D applies pretrained…

Computer Vision and Pattern Recognition · Computer Science 2023-03-29 Hiromichi Kamata , Yuiko Sakuma , Akio Hayakawa , Masato Ishii , Takuya Narihira

Given an original image, image editing aims to generate an image that align with the provided instruction. The challenges are to accept multimodal inputs as instructions and a scarcity of high-quality training data, including crucial…

Computer Vision and Pattern Recognition · Computer Science 2024-12-17 Zhen Han , Chaojie Mao , Zeyinzi Jiang , Yulin Pan , Jingfeng Zhang

Recent advances in visual generative models have enabled high-fidelity image editing guided by human instructions. However, these models often struggle with complex instructions involving combinatorial editing operations or inter-step…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Zilai Zeng , Mingdeng Cao , Zijie Li , Xiaochen Lian , Yichun Shi , Peihao Zhu , Chen Sun , Peng Wang

When obtaining visual illustrations from text descriptions, today's methods take a description with a single text context - a caption, or an action description - and retrieve or generate the matching visual context. However, prior work does…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Chi Hsuan Wu , Kumar Ashutosh , Kristen Grauman

Comparing a user video to a reference how-to video is a key requirement for AR/VR technology delivering personalized assistance tailored to the user's progress. However, current approaches for language-based assistance can only answer…

Computer Vision and Pattern Recognition · Computer Science 2024-07-01 Tushar Nagarajan , Lorenzo Torresani

Recent advances in generative diffusion models have enabled text-controlled synthesis of realistic and diverse images with impressive quality. Despite these remarkable advances, the application of text-to-image generative models in computer…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Yulu Gan , Sungwoo Park , Alexander Schubert , Anthony Philippakis , Ahmed M. Alaa

Recent advancements in instruction-based image editing and subject-driven generation have garnered significant attention, yet both tasks still face limitations in meeting practical user needs. Instruction-based editing relies solely on…

Computer Vision and Pattern Recognition · Computer Science 2025-10-09 Bin Xia , Bohao Peng , Yuechen Zhang , Junjia Huang , Jiyang Liu , Jingyao Li , Haoru Tan , Sitong Wu , Chengyao Wang , Yitong Wang , Xinglong Wu , Bei Yu , Jiaya Jia

Cooking requires not only following instructions but also understanding, executing, and monitoring each step - a process that can be challenging without visual guidance. Although recipe images and videos offer helpful cues, they often lack…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 Oleh Kuzyk , Zuoyue Li , Marc Pollefeys , Xi Wang

Conditional text-to-image generation is an active area of research, with many possible applications. Existing research has primarily focused on generating a single image from available conditioning information in one step. One practical…

Computer Vision and Pattern Recognition · Computer Science 2019-09-24 Alaaeldin El-Nouby , Shikhar Sharma , Hannes Schulz , Devon Hjelm , Layla El Asri , Samira Ebrahimi Kahou , Yoshua Bengio , Graham W. Taylor

In recent years, synthetic visual instructions by generative language model have demonstrated plausible text generation performance on the visual question-answering tasks. However, challenges persist in the hallucination of generative…

Computer Vision and Pattern Recognition · Computer Science 2024-02-14 Sungguk Cha , Jusung Lee , Younghyun Lee , Cheoljong Yang

There are substantial instructional videos on the Internet, which provide us tutorials for completing various tasks. Existing instructional video datasets only focus on specific steps at the video level, lacking experiential guidelines at…

Computer Vision and Pattern Recognition · Computer Science 2024-06-27 Jiafeng Liang , Shixin Jiang , Zekun Wang , Haojie Pan , Zerui Chen , Zheng Chu , Ming Liu , Ruiji Fu , Zhongyuan Wang , Bing Qin

Understanding what sequence of steps are needed to complete a goal can help artificial intelligence systems reason about human activities. Past work in NLP has examined the task of goal-step inference for text. We introduce the visual…

Computer Vision and Pattern Recognition · Computer Science 2021-09-13 Yue Yang , Artemis Panagopoulou , Qing Lyu , Li Zhang , Mark Yatskar , Chris Callison-Burch

Generating videos for visual storytelling can be a tedious and complex process that typically requires either live-action filming or graphics animation rendering. To bypass these challenges, our key idea is to utilize the abundance of…

Computer Vision and Pattern Recognition · Computer Science 2023-07-14 Yingqing He , Menghan Xia , Haoxin Chen , Xiaodong Cun , Yuan Gong , Jinbo Xing , Yong Zhang , Xintao Wang , Chao Weng , Ying Shan , Qifeng Chen

We are interested in the generation of navigation instructions, either in their own right or as training material for robotic navigation task. In this paper, we propose a new approach to navigation instruction generation by framing the…

Computation and Language · Computer Science 2024-03-29 Chengzu Li , Chao Zhang , Simone Teufel , Rama Sanand Doddipatla , Svetlana Stoyanchev

We introduce a large-scale dataset for instruction-guided vector image editing, consisting of over 270,000 pairs of SVG images paired with natural language edit instructions. Our dataset enables training and evaluation of models that modify…

Machine Learning · Computer Science 2025-06-23 Josef Kuchař , Marek Kadlčík , Michal Spiegel , Michal Štefánik