Visual Realism Evaluation Using Human Feedback Loops
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Automating the modification of large numbers of visual contents to achieve high-quality, optimal results is challenging, especially in determining the degree of realism in artificially generated visual content.
Innovation Solution
Systems and methods for attributing generated visual content to training examples, transforming non-realistic virtual environments to realistic ones, and determining the degree of realism using machine learning algorithms and generative models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If machine learning algorithms and generative models are used to automate visual content modification, then productivity is improved, but measurement precision of realism degree deteriorates
Solution Approach 1:
The patent introduces an intermediary evaluation system that bridges automated generation and human judgment. This system presents generated content to multiple users, collects their realism assessments, and aggregates this feedback to objectively determine the degree of realism. The intermediary process transforms subjective human perceptions into measurable data that can guide further automated modifications.
Solution Approach 2:
The system implements a feedback loop where user reactions to generated visual content are collected and used to update the generative model. This feedback mechanism allows the system to learn from human judgments and progressively improve its ability to generate realistic content, resolving the contradiction between automation and measurement precision by making the measurement results actionable.
2Measurement precision
If user reactions are collected to determine realism degree, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The system performs preliminary actions by pre-presenting generated content to users before final evaluation. This allows the system to gather baseline realism assessments early in the process, enabling faster subsequent iterations. The preliminary user feedback is used to make immediate adjustments, reducing the need for extensive re-evaluation later.
Solution Approach 2:
The evaluation process is structured as periodic action rather than continuous monitoring. Users are presented with generated content at specific intervals, and their reactions are collected in batches. This periodic approach balances the need for accurate measurement with time constraints, allowing the system to efficiently process multiple generations without requiring constant user input.
3Reliability
If data records are updated based on attribution, then reliability is improved, but device complexity increases
Solution Approach 1:
The data record system is designed with multi-functionality to justify its complexity. The same attribution mechanism serves multiple purposes: tracking which training examples influenced generated content, measuring realism degree through user feedback, and guiding future generation improvements. This universal application of the data tracking system maximizes its value relative to its complexity cost.
Data Source
AI summary
Systems, methods and non-transitory computer readable media for determining a degree of realism of an artificially generated visual content are provided. Artificially generated visual contents including a particular artificially generated visual content may be accessed. Captured visual contents may be accessed. For each person of a plurality of persons, a mix of visual contents including at least one artificially generated visual content and at least one captured visual content may be presented to the person, where the mix includes the particular artificially generated visual content. A reaction to the presentation indicative of whether the person believes that visual contents are artificially generated may be received. A degree of realism of the particular artificially generated visual content may be determined based on the reactions.