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Establishing dense correspondences between a pair of images is an important and general problem. However, dense flow estimation is often inaccurate in the case of large displacements or homogeneous regions. For most applications and…

Computer Vision and Pattern Recognition · Computer Science 2021-04-02 Prune Truong , Martin Danelljan , Luc Van Gool , Radu Timofte

We address the problem of semantic correspondence, that is, establishing a dense flow field between images depicting different instances of the same object or scene category. We propose to use images annotated with binary foreground masks…

Computer Vision and Pattern Recognition · Computer Science 2020-07-23 Junghyup Lee , Dohyung Kim , Wonkyung Lee , Jean Ponce , Bumsub Ham

In this paper, we address the problem of building dense correspondences between human images under arbitrary camera viewpoints and body poses. Prior art either assumes small motion between frames or relies on local descriptors, which cannot…

Computer Vision and Pattern Recognition · Computer Science 2021-03-30 Feitong Tan , Danhang Tang , Mingsong Dou , Kaiwen Guo , Rohit Pandey , Cem Keskin , Ruofei Du , Deqing Sun , Sofien Bouaziz , Sean Fanello , Ping Tan , Yinda Zhang

Sketching is a powerful artistic technique for capturing essential visual information about real-world objects and has increasingly attracted attention in image synthesis research. However, the field lacks a unified benchmark to evaluate…

Computer Vision and Pattern Recognition · Computer Science 2025-04-10 Xingyue Lin , Xingjian Hu , Shuai Peng , Jianhua Zhu , Liangcai Gao

We address the problem of semantic correspondence, that is, establishing a dense flow field between images depicting different instances of the same object or scene category. We propose to use images annotated with binary foreground masks…

Computer Vision and Pattern Recognition · Computer Science 2019-04-08 Junghyup Lee , Dohyung Kim , Jean Ponce , Bumsub Ham

Multiple sketch datasets have been proposed to understand how people draw 3D objects. However, such datasets are often of small scale and cover a small set of objects or categories. In addition, these datasets contain freehand sketches…

Computer Vision and Pattern Recognition · Computer Science 2022-09-20 Chufeng Xiao , Wanchao Su , Jing Liao , Zhouhui Lian , Yi-Zhe Song , Hongbo Fu

In this work, we investigate the problem of sketch-based object localization on natural images, where given a crude hand-drawn sketch of an object, the goal is to localize all the instances of the same object on the target image. This…

Computer Vision and Pattern Recognition · Computer Science 2023-03-16 Aditay Tripathi , Anand Mishra , Anirban Chakraborty

Determining dense semantic correspondences across objects and scenes is a difficult problem that underpins many higher-level computer vision algorithms. Unlike canonical dense correspondence problems which consider images that are spatially…

Computer Vision and Pattern Recognition · Computer Science 2015-05-18 Hilton Bristow , Jack Valmadre , Simon Lucey

Sketching is used as a ubiquitous tool of expression by novices and experts alike. In this thesis I explore two methods that help a system provide a geometric machine-understanding of sketches, and in-turn help a user accomplish a…

Computer Vision and Pattern Recognition · Computer Science 2022-04-15 Raghav Brahmadesam Venkataramaiyer

Spatial-query-by-sketch is an intuitive tool to explore human spatial knowledge about geographic environments and to support communication with scene database queries. However, traditional sketch-based spatial search methods perform…

Computer Vision and Pattern Recognition · Computer Science 2022-02-11 Danhuai Guo , Shiyin Ge , Shu Zhang , Song Gao , Ran Tao , Yangang Wang

In this paper, we tackle for the first time, the problem of self-supervised representation learning for free-hand sketches. This importantly addresses a common problem faced by the sketch community -- that annotated supervisory data are…

Computer Vision and Pattern Recognition · Computer Science 2020-02-04 Peng Xu , Zeyu Song , Qiyue Yin , Yi-Zhe Song , Liang Wang

We present recurrent transformer networks (RTNs) for obtaining dense correspondences between semantically similar images. Our networks accomplish this through an iterative process of estimating spatial transformations between the input…

Computer Vision and Pattern Recognition · Computer Science 2018-10-30 Seungryong Kim , Stephen Lin , Sangryul Jeon , Dongbo Min , Kwanghoon Sohn

We present a system for identifying conceptual shifts between visual categories, which will form the basis for a co-creative drawing system to help users draw more creative sketches. The system recognizes human sketches and matches them to…

Machine Learning · Computer Science 2018-01-12 Pegah Karimi , Nicholas Davis , Kazjon Grace , Mary Lou Maher

Decades of psychological research have been aimed at modeling how people learn features and categories. The empirical validation of these theories is often based on artificial stimuli with simple representations. Recently, deep neural…

Computer Vision and Pattern Recognition · Computer Science 2018-07-25 Joshua C. Peterson , Joshua T. Abbott , Thomas L. Griffiths

Semantic correspondence is the problem of establishing correspondences across images depicting different instances of the same object or scene class. One of recent approaches to this problem is to estimate parameters of a global…

Computer Vision and Pattern Recognition · Computer Science 2018-10-29 Paul Hongsuck Seo , Jongmin Lee , Deunsol Jung , Bohyung Han , Minsu Cho

Sketch-based face recognition is an interesting task in vision and multimedia research, yet it is quite challenging due to the great difference between face photos and sketches. In this paper, we propose a novel approach for photo-sketch…

Computer Vision and Pattern Recognition · Computer Science 2015-04-14 Liliang Zhang , Liang Lin , Xian Wu , Shengyong Ding , Lei Zhang

Given an abstract, deformed, ordinary sketch from untrained amateurs like you and me, this paper turns it into a photorealistic image - just like those shown in Fig. 1(a), all non-cherry-picked. We differ significantly from prior art in…

Computer Vision and Pattern Recognition · Computer Science 2023-03-31 Subhadeep Koley , Ayan Kumar Bhunia , Aneeshan Sain , Pinaki Nath Chowdhury , Tao Xiang , Yi-Zhe Song

Researchers have explored various ways to generate realistic images from freehand sketches, e.g., for objects and human faces. However, how to generate realistic human body images from sketches is still a challenging problem. It is, first…

Computer Vision and Pattern Recognition · Computer Science 2022-05-23 Xian Wu , Chen Wang , Hongbo Fu , Ariel Shamir , Song-Hai Zhang , Shi-Min Hu

The human ability to recognize when an object belongs or does not belong to a particular vision task outperforms all open set recognition algorithms. Human perception as measured by the methods and procedures of visual psychophysics from…

Computer Vision and Pattern Recognition · Computer Science 2023-04-26 Jin Huang , Derek Prijatelj , Justin Dulay , Walter Scheirer

Proliferation of touch-based devices has made sketch-based image retrieval practical. While many methods exist for sketch-based object detection/image retrieval on small datasets, relatively less work has been done on large (web)-scale…

Computer Vision and Pattern Recognition · Computer Science 2015-11-03 Sarthak Parui , Anurag Mittal