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Hello,
Thank you for sharing the code for your project. I would like to reproduce your results on Multi-Object-Fetch tasks and kindly ask for clarification on a few questions:
- It is mentioned in the paper that you trained the SAVi model on a dataset of 1 million frames. Did you train an individual model for every task, or did you train one model for all Reach* tasks, one model for all Push* tasks, and one model for all Pick* tasks?
- According to the video on the project’s site https://slot-latent-dynamics.github.io/ and Figure 1, the agent is tasked with moving the green cube to the target location in Push-Specific and Pick-Specific tasks. However, I did not find pre-defined MOF environments for these tasks. It looks like the most suitable candidates are PushRed_0to4Distractors_Dense-v1 and PickRed_0to4Distractors_Dense-v1, where the agent is tasked with moving the red cube, not the green one. Did you use custom environments PushGreen and PickGreen in your experiments instead of PushRed and PickRed?
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