학회 정보

WACV 2027: IEEE/CVF Winter Conference on Applications of Computer Vision

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회원가입 로그인
투고 마감일:
2026-08-28 마감됨
통보일:
2026-10-09
개최일:
2027-01-04
개최지:
Buena Vista, Florida, USA
개최 횟수:
ICORE: A   QUALIS: B1   조회: 46118   팔로우: 32   참가: 2
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WACV
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회반 지수 (CP-I)

58.5 / 100
전체 5,759개 중 663위 · 상위 12%

컴퓨터 비전·패턴 인식 분야 246개 중 24위

학술적 인정 (35%)
88
투고 선별성 (20%) 데이터 없음 — 중립 기준값 50점으로 계산 —
개최 횟수 (20%)
19
커뮤니티 관심도 (10%)
58
공개 자료 충실도 (15%)
55

사용한 입력: 수록 등급: ICORE A, QUALIS B1 · 확인되는 개최 횟수: 1 · 회반에서 팔로우 중인 연구자: 32명 · 지난 24개월 동안 이 페이지를 연 연구자: 23명

공개 자료에서 빠진 항목: 역대 게재율 (+4.5) · 최우수 논문 기록 (+2.3)
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신뢰도 80% — 점수 중 중립 기준값이 아니라 실제 관측된 데이터에 근거한 비율. 이 점수는 어떻게 계산되나 · 전체 순위 보기 · 알고리즘 버전 1.2 · 산출일 2026-10-24

논문 모집

WACV 2027 (IEEE/CVF Winter Conference on Applications of Computer Vision) is a ICORE A / QUALIS B1 conference held in Buena Vista, Florida, USA on 2027-01-04. The paper submission deadline is 2026-08-28. Acceptance notifications are sent on 2026-10-09.

IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) provides a forum for computer vision researchers working on practical applications and innovative algorithms to share their latest developments. Applications Track WACV 2027 solicits high-quality, original submissions describing research in computer vision, with a particular emphasis on systems and applications with significant, interesting vision components. Application areas include, but are not limited to: Agriculture Animals and Insects Arts, games, and social media Autonomous driving Biomedical, healthcare, and medicine Commercial and retail Education Embedded sensing and real-time techniques Environmental monitoring, climate change, and ecology Food science and nutrition Psychology and cognitive science Remote sensing Robotics Smartphones and end-user devices Social good Structural engineering and civil engineering Virtual and augmented reality Visualization Algorithms Track Authors are also encouraged to submit more traditional computer vision algorithms papers. Topics of interest include, but are not limited to: 3D computer vision Adversarial learning, adversarial attack, and defense methods Biometrics, face, gesture, and body pose Computational photography Generative models for image, video, 3D, etc. Explainable, fair, accountable, privacy-preserving, and ethical computer vision Image recognition and understanding (object detection, categorization, segmentation, scene modeling, visual reasoning) Low-level and physics-based vision Machine learning architectures, formulations, and algorithms (including transfer, low-shot, semi-, self-, and unsupervised learning) Video recognition and understanding (tracking, action recognition, etc.) Vision + language and/or other modalities Foundation models for downstream vision tasks Evaluations & Datasets Track Authors are also encouraged to submit papers to the Evaluations & Datasets (E&D) Track. These submissions must advance the science and practice of evaluation in computer vision including the development and use of datasets and other resources. Topics of interest include, but are not limited to: Analysis of strengths, limitations, or failure modes of existing benchmarks or evaluation practices Study benchmark saturation or overfitting and their impact on scientific conclusions Compare evaluation designs and demonstrate how different assumptions lead to different results or conclusions Provide rigorous reproduction, auditing, and stress-testing of prior evaluations Propose new evaluation protocols, practices, or methodologies Conduct human- or interaction-centered evaluations (e.g., user studies, red-teaming) Introduce datasets and clearly explain their scope, assumptions, limitations, and how they are intended to support or shape evaluative claims across the computer vision lifecycle Contribute tools, analyses, or frameworks that improve how evaluative claims are constructed or interpreted Present negative results, critical analyses, and use-case-inspired evaluations New datasets and dataset collections Audits of existing datasets Benchmarks on new or existing datasets, benchmarking tools, and methodologies Systematic analyses of systems on novel datasets
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관련 저널

CCF정식 명칭영향력 지수출판사ISSN
CNeurocomputing6.5Elsevier0925-2312
CMachine Vision and Applications2.3Springer0932-8092
AIEEE Transactions on Multimedia9.7IEEE1520-9210
CKnowledge-Based Systems7.2Elsevier0950-7051
BSoftware & Systems Modeling3.2Springer1619-1366
AIEEE Transactions on Computers3.8IEEE0018-9340
CFuture Generation Computer Systems5.9Elsevier0167-739X
CPattern Recognition Letters3.9Elsevier0167-8655
BPattern Recognition7.6Elsevier0031-3203
IEEE Access3.6IEEE2169-3536

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