We validate the presented approach by producing dense pixel-level semantic annotations for 25 thousand images synthesized by a photorealistic open-world computer game. This enables rapid propagation of semantic labels within and across images synthesized by the game, with no access to the source code or the content. Although the source code and the internal operation of commercial games are inaccessible, we show that associations between image patches can be reconstructed from the communication between the game and the graphics hardware. In this paper, we present an approach to rapidly creating pixel-accurate semantic label maps for images extracted from modern computer games.
Unfortunately, creating large datasets with pixel-level labels has been extremely costly due to the amount of human effort required. Recent progress in computer vision has been driven by high-capacity models trained on large datasets.
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