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We propose a method for scene-level sketch-to-photo synthesis with text guidance. Although object-level sketch-to-photo synthesis has been widely studied, whole-scene synthesis is still challenging without reference photos that adequately…

Computer Vision and Pattern Recognition · Computer Science 2023-02-15 AprilPyone MaungMaung , Makoto Shing , Kentaro Mitsui , Kei Sawada , Fumio Okura

Recently, text-to-3D approaches have achieved high-fidelity 3D content generation using text description. However, the generated objects are stochastic and lack fine-grained control. Sketches provide a cheap approach to introduce such…

Computer Vision and Pattern Recognition · Computer Science 2024-01-30 Minglin Chen , Weihao Yuan , Yukun Wang , Zhe Sheng , Yisheng He , Zilong Dong , Liefeng Bo , Yulan Guo

Modern data stream applications demand memory-efficient solutions for accurately tracking frequent items, such as heavy hitters and heavy changers, under strict resource constraints. Traditional sketches face inherent accuracy-memory…

Databases · Computer Science 2025-05-20 Zicang Xu , Yuxuan Tian , Yuhan Wu , Tong Yang

Sketches make an intuitive and powerful visual expression as they are fast executed freehand drawings. We present a method for synthesizing realistic photos from scene sketches. Without the need for sketch and photo pairs, our framework…

Computer Vision and Pattern Recognition · Computer Science 2022-09-08 Jiayun Wang , Sangryul Jeon , Stella X. Yu , Xi Zhang , Himanshu Arora , Yu Lou

Significant progress has recently been made in creative applications of large pre-trained models for downstream tasks in 3D vision, such as text-to-shape generation. This motivates our investigation of how these pre-trained models can be…

Computer Vision and Pattern Recognition · Computer Science 2023-07-11 Aditya Sanghi , Pradeep Kumar Jayaraman , Arianna Rampini , Joseph Lambourne , Hooman Shayani , Evan Atherton , Saeid Asgari Taghanaki

Current sketch extraction methods either require extensive training or fail to capture a wide range of artistic styles, limiting their practical applicability and versatility. We introduce Mixture-of-Self-Attention (MixSA), a training-free…

Computer Vision and Pattern Recognition · Computer Science 2025-01-03 Rui Yang , Xiaojun Wu , Shengfeng He

Sketch-to-image (S2I) translation plays an important role in image synthesis and manipulation tasks, such as photo editing and colorization. Some specific S2I translation including sketch-to-photo and sketch-to-painting can be used as…

Computer Vision and Pattern Recognition · Computer Science 2020-06-19 Jialu Huang , Jing Liao , Zhifeng Tan , Sam Kwong

Designing stylized cinemagraphs is challenging due to the difficulty in customizing complex and expressive flow elements. To achieve intuitive and detailed control of the generated cinemagraphs, sketches provide a feasible solution to…

Computer Vision and Pattern Recognition · Computer Science 2026-03-12 Hao Jin , Hengyuan Chang , Xiaoxuan Xie , Zhengyang Wang , Xusheng Du , Shaojun Hu , Haoran Xie

We propose a novel image-to-pencil translation method that could not only generate high-quality pencil sketches but also offer the drawing process. Existing pencil sketch algorithms are based on texture rendering rather than the direct…

Computer Vision and Pattern Recognition · Computer Science 2020-12-17 Zhengyan Tong , Xuanhong Chen , Bingbing Ni , Xiaohang Wang

Facial sketches are both a concise way of showing the identity of a person and a means to express artistic intention. While a few techniques have recently emerged that allow sketches to be extracted in different styles, they typically rely…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Kwan Yun , Kwanggyoon Seo , Chang Wook Seo , Soyeon Yoon , Seongcheol Kim , Soohyun Ji , Amirsaman Ashtari , Junyong Noh

3D Content Generation is at the heart of many computer graphics applications, including video gaming, film-making, virtual and augmented reality, etc. This paper proposes a novel deep-learning based approach for automatically generating…

Computer Vision and Pattern Recognition · Computer Science 2026-02-09 Yongzhi Xu , Yonhon Ng , Yifu Wang , Inkyu Sa , Yunfei Duan , Zhenhong Sun , Yang Li , Pan Ji , Hongdong Li

Recent advancements in text-to-image generative models have demonstrated a remarkable ability to capture a deep semantic understanding of images. In this work, we leverage this semantic knowledge to transfer the visual appearance between…

Computer Vision and Pattern Recognition · Computer Science 2023-11-07 Yuval Alaluf , Daniel Garibi , Or Patashnik , Hadar Averbuch-Elor , Daniel Cohen-Or

Recent advances in diffusion models have significantly improved text-to-image (T2I) generation, but they often struggle to balance fine-grained precision with high-level control. Methods like ControlNet and T2I-Adapter excel at following…

Computer Vision and Pattern Recognition · Computer Science 2025-04-11 Pouyan Navard , Amin Karimi Monsefi , Mengxi Zhou , Wei-Lun Chao , Alper Yilmaz , Rajiv Ramnath

Sketches, with their expressive potential, allow humans to convey the essence of an object through even a rough contour. For the first time, we harness this expressive potential to improve segmentation performance in challenging tasks like…

Computer Vision and Pattern Recognition · Computer Science 2025-02-03 Ying Zang , Runlong Cao , Jianqi Zhang , Yidong Han , Ziyue Cao , Wenjun Hu , Didi Zhu , Lanyun Zhu , Zejian Li , Deyi Ji , Tianrun Chen

Visual illusions traditionally rely on spatial manipulations such as multi-view consistency. In this work, we introduce Progressive Semantic Illusions, a novel vector sketching task where a single sketch undergoes a dramatic semantic…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Huai-Hsun Cheng , Siang-Ling Zhang , Yu-Lun Liu

Iteratively refining and critiquing sketches are crucial steps to developing effective designs. We introduce Scones, a mixed-initiative, machine-learning-driven system that enables users to iteratively author sketches from text…

Human-Computer Interaction · Computer Science 2020-05-19 Forrest Huang , Eldon Schoop , David Ha , John Canny

Sketch editing requires jointly handling high-level semantic changes and precise local redrawing, a combination that is particularly challenging for sparse, style-sensitive line art. Unlike natural images, sketches rely on minimal visual…

Computer Vision and Pattern Recognition · Computer Science 2026-05-27 Han Zou , Yan Zhang , Ruiqi Yu , Cong Xie , Jie Huang , Zhenpeng Zhan

The ability to semantically interpret hand-drawn line sketches, although very challenging, can pave way for novel applications in multimedia. We propose SketchParse, the first deep-network architecture for fully automatic parsing of…

Computer Vision and Pattern Recognition · Computer Science 2017-09-06 Ravi Kiran Sarvadevabhatla , Isht Dwivedi , Abhijat Biswas , Sahil Manocha , R. Venkatesh Babu

Sketching provides an intuitive way to convey dynamic intent in animation authoring (i.e., how elements change over time and space), making it a natural medium for automatic content creation. Yet existing approaches often constrain sketches…

Human-Computer Interaction · Computer Science 2026-01-29 Boyu Li , Lin-Ping Yuan , Zeyu Wang , Hongbo Fu

In this work, we develop intuitive controls for editing the style of 3D objects. Our framework, Text2Mesh, stylizes a 3D mesh by predicting color and local geometric details which conform to a target text prompt. We consider a disentangled…

Computer Vision and Pattern Recognition · Computer Science 2021-12-07 Oscar Michel , Roi Bar-On , Richard Liu , Sagie Benaim , Rana Hanocka