Learn about scene bias in action recognition and explore techniques to mitigate its effects in this 22-minute conference talk from the University of Central Florida. Delve into the motivation behind addressing representation bias, understand its definition and measurement, and examine real-world examples. Discover proposed solutions, including adversary training and artificial occlusion, and explore related works in the field. Gain insights into testing methods, various data sets used for analysis, and quantitative results in action recognition. Examine scene representation bias comparisons and class activation maps before reaching the conclusion on mitigating scene bias in action recognition systems.