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Found 3 papers, 1 papers with code
Knowing the Distance: Understanding the Gap Between Synthetic and Real Data For Face Parsing
Our study highlights the importance of content diversity in synthetic datasets and challenges the notion that the photorealism gap is the most critical factor affecting the performance of computer vision models trained on synthetic data.
Hands-Up: Leveraging Synthetic Data for Hands-On-Wheel Detection
Over the past few years there has been major progress in the field of synthetic data generation using simulation based techniques.
Generalizing Across Multi-Objective Reward Functions in Deep Reinforcement Learning
The Hindsight Experience Replay algorithm developed by Andrychowicz et al. (2017) does just this, and learns to generalize across a distribution of sparse, goal-based rewards.
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