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VP-HBA 2021: Video Processing for Human Behavioral Analysis Track

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Submission Date:
2020-10-12 Extended
Notification Date:
2020-11-24
Conference Date:
2021-03-22
Location:
Gwangju, Korea
Viewed: 11992   Tracked: 0   Attend: 0

Conference Partner Index (CP-I)

42.1 / 100
Ranked #4,126 of 5,680 conferences · Top 73%

#209 of 243 in Computer Vision & Pattern Recognition

Limited evidence: this conference is not listed in CCF / ICORE / QUALIS and has no acceptance-rate data on file, so most of the score falls back to the neutral baseline.
Academic recognition (35%) No data - scored at the neutral baseline of 50
Submission selectivity (20%) No data - scored at the neutral baseline of 50
Editions held (20%) No data - scored at the neutral baseline of 50
Community attention (10%)
8
Public record completeness (15%)
25

Inputs used: Researchers who opened this page in the past 24 months: 2

Missing from the public record: Historical acceptance rates (+4.5) · Past editions (+3.0) · Best-paper records (+2.3)
Organizers can add these from this page after claiming the conference; scores are recomputed nightly. How to raise this score

Confidence 25% - the share of the score backed by observed data rather than the neutral baseline. How this score is calculated · Browse the ranking · Algorithm version 1.1 · Computed 2026-09-12

Call For Papers

VP-HBA 2021 (Video Processing for Human Behavioral Analysis Track) is an academic conference held in Gwangju, Korea on 2021-03-22. The paper submission deadline is 2020-10-12 (extended). Acceptance notifications are sent on 2020-11-24.

SUBMISSION DATE EXTENDED: 2020-10-12 The 36th ACM/SIGAPP Symposium on Applied Computing (SAC 2021) has been a primary gathering forum for applied computer scientists, computer engineers, software engineers, and application developers from around the world. SAC 2021 is sponsored by the ACM Special Interest Group on Applied Computing (SIGAPP), and will be held in Gwangju, Korea. The technical track on Video Processing for Human Behavioral Analysis (VP-HBA 2021) is at its second edition and will be organized within SAC 2021. Description Aiming at bridging the gap between human and machine vision, video signal is probably the main cue that multimodal machine learning and pattern recognition tools rely on. Among the difficult tasks dealt with in this domain, human behavior understanding is surely accounted a challenging one. Activities such as action recognition, affective computing, human computer interaction, urban analytics, or applications in health, security, robotics and video games are undoubtedly well-established topics in which computer vision plays a fundamental role. Studying human-human or human-computer interactions has also attracted increasing attention in recent years due to its widespread meaning and applications. Furthermore, the advancements in computer vision for social behavior analysis can bring ubiquitous changes in the society. However, despite significant research progress, the automated understanding of a wide range of human activities from visual as well as multimodal data still remains a source of challenging topics. This track mainly intends to focus on all aspects of computer vision, pattern recognition and machine intelligence devoted to the automatic analysis of human behavior by applying recent or novel video and multimodal data processing techniques. Topics include but are not limited to - Human behavior analysis from visual and multimodal information - Information fusion for the analysis of human behavior - Affective computing and interaction - Cognitive interaction understanding - Visual attention models and systems - Crowd and social behavior understanding - Human and group action recognition - Human-machine interaction - Databases for human-human interaction - Scene understanding - Automatic tracking in videos - Social networks analysis - Modeling and simulation of human interactions - Multimodal dyadic interaction - Artificial intelligence for human interaction analysis - Pervasive computing for human interaction understanding - Computer vision for health emergencies - Gesture and gait analysis - Applications of behavior analysis methods, e.g., in medicine, sports and games, well-being, security, environment
Last updated by Jianyi Lin on

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