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VISAPP 2027: International Conference on Computer Vision Theory and Applications

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VISAPP
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截稿日期:
2026-09-15 明天截止
通知日期:
2026-11-13
会议日期:
2027-02-26
会议地点:
Valletta, Malta
届数:
QUALIS: B3   浏览: 47307   关注: 18   参加: 7

会伴指数 (CP-I)

62.7 / 100
全站第 504 名 / 共 5,681 个会议 · 前 9%

计算机视觉与模式识别 第 14 / 244

学术认可 (35%)
60
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入 —
会议传承 (20%)
84
社区关注 (10%)
43
资料公开度 (15%)
70

用到的输入: 收录等级：QUALIS B3 · 有据可查的届次：22 · 在会伴关注它的研究者：18 人 · 过去 24 个月打开过本页的研究者：6 人

公开资料里还缺: 历年录用率 (+4.5)
主办方认领本会议后，可直接在这一页补上；分数每晚重算。如何提升这个分数

置信度 80% —— 分数中有多大比例来自实际观测到的数据，而不是中性基准。 这个分数是怎么算出来的 · 查看完整榜单 · 算法版本 1.1 · 算于 2026-09-13

征稿

VISAPP 2027 (International Conference on Computer Vision Theory and Applications) is a QUALIS B3 conference held in Valletta, Malta on 2027-02-26. The paper submission deadline is 2026-09-15. Acceptance notifications are sent on 2026-11-13.

SCOPE The International Conference on Computer Vision Theory and Applications aims at becoming a major point of contact between researchers, engineers and practitioners on the area of computer vision methodology and systems, and their application. Five simultaneous tracks will be held, covering all different aspects related to computer vision: Foundations & Representation Learning; Recognition & Detection; Low-level Vision & Computational Imaging; and 3D Vision, Motion, Robotics, Application & Systems. We welcome papers describing original work in any of the areas listed below. Papers describing advanced prototypes, systems, tools and techniques as well as general survey papers indicating future directions are also encouraged. Paper acceptance will be based on quality, relevance to the conference themes and originality. The conference program will include both oral and poster presentations. Special sessions, dedicated to case-studies and commercial presentations, as well as technical tutorials, dedicated to technical/scientific topics, are also envisaged. CONFERENCE AREAS The last decade has seen a revolution in the theory and application of Artificial Intelligence and Machine Learning in Computer Vision. In this conference edition, we look at advanced in Computer Vision based on Machine Learning methods. Each of these topic areas is expanded below but the sub-topics list is not exhaustive. Papers may address one or more of the listed sub-topics, although authors should not feel limited by them. Unlisted but related sub-topics are also acceptable, provided they fit in one of the following main topic areas: 1. FOUNDATIONS AND REPRESENTATION LEARNING 2. RECOGNITION AND DETECTION 3. LOW-LEVEL VISION AND COMPUTATIONAL IMAGING 4. 3D VISION, MOTION, ROBOTICS, APPLICATION AND SYSTEMS AREA 1: FOUNDATIONS AND REPRESENTATION LEARNING Deep Learning for Visual Understanding Domain Adaptation Generative AI Machine Learning Technologies for Vision Multi-task learning Self-supervised Learning Transfer Learning AREA 2: RECOGNITION AND DETECTION Categorization and Scene Understanding Event and Human Activity Recognition Face and Expression Recognition Few-Shot Learning Object and Face Recognition Object Detection and Localization Segmentation and Grouping AREA 3: LOW-LEVEL VISION AND COMPUTATIONAL IMAGING Color and Texture Analyses Features Extraction Image Enhancement and Restoration Image Formation, Acquisition Devices and Sensors Image Registration Multimodal and Multi-Sensor Models of Image Formation Shape Representation and Matching Visual Attention and Image Saliency AREA 4: 3D VISION, MOTION, ROBOTICS, APPLICATION AND SYSTEMS 3D Deep Learning Assistive Computer Vision Content-Based Indexing, Search, and Retrieval Deep Learning for Tracking Entertainment Imaging Applications Human and Computer Interaction Image-Based Modeling and 3D Reconstruction Medical Image Applications Mobile Vision Optical Flow and Motion Analyses Stereo Vision and Structure from Motion Tracking and Visual Navigation Video Surveillance and Event Detection Vision for Robotics
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C58.0ICPRAMInternational Conference on Pattern Recognition Applications and Methods2026-09-152027-02-20

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