With growing global security concerns, biometric-based authentication and identification have become indispensable due to their reliability and robustness. Beyond physical biometrics, behavior understanding is emerging as a critical domain, aiming to interpret complex behavioral patterns that arise during interactions. Integrating both biometric and behavioral insights can lead to more secure, adaptive, and context-aware identity verification systems. Computer vision plays a pivotal role in analyzing and synthesizing biometric, identity, and behavior data. Recent advancements in research, driven by deep learning and multimodal analysis, have significantly expanded the field. However, numerous challenges remain, including effective joint modeling of multimodal cues occurring at different time scales, handling the inherent uncertainty of machine-detectable behavioral evidence, and addressing long-term dependencies in human behavior and identity recognition. This workshop aims to bring together leading researchers, industry experts, and government agencies to discuss the latest breakthroughs. It will serve as a platform to explore cutting-edge solutions, share innovative methodologies, and address the open challenges in this evolving field.