Data alternatives for pretraining computer vision models

Not only did a classifier pre-trained on Task2Sim's fake images perform as well as a model trained on real ImageNet photos, it also outperformed a rival trained on images generated with random simulation parameters. Task2Sim even transferred its know-how to entirely new tasks, creating images to teach a classifier how to identify cactuses and hand-drawn numbers. "The more tasks you use during training, the more generalizable the model will be," Feris said. A related tool, SimVQA,2 also appearing at CVPR, generates synthetic text and images for training robot agents to reason about the visual world. In a typical visual-reasoning task, an agent might be asked to count the number of chairs at a table or identify the color of a bouquet of flowers.