From ad2bf635881755c358763ea91924834cd82704c3 Mon Sep 17 00:00:00 2001 From: Nolan Wagener Date: Thu, 22 Aug 2024 10:24:50 -0400 Subject: [PATCH] Update README.md Add example projects that have used MoCapAct --- README.md | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/README.md b/README.md index 9313ae2..ef39a73 100644 --- a/README.md +++ b/README.md @@ -346,6 +346,12 @@ The [`D4RLDataset`](https://github.com/microsoft/MoCapAct/blob/main/mocapact/off For small enough instantiations of the datasets that fit into memory, the user can use `D4RLDataset.get_in_memory_rollouts()` to load a batch of transitions into memory. For instantiations that do not fit into memory (e.g., the entire MoCapAct dataset), the user can use the dataset as a PyTorch `Dataset` by using an iterator over the transitions obtained by using `__getitem__()`. +## Example Projects that Have Used MoCapAct +- H-GAP: Humanoid Control with a Generalist Planner, by Zhengyao Jiang, Yingchen Xu, et al. ([Paper](https://arxiv.org/abs/2312.02682), [Website](https://yingchenxu.com/hgap), [Code](https://github.com/facebookresearch/hgap)) +- Leveraging Demonstrations with Latent Space Priors, by Jonas Gehring et al. ([Paper](https://arxiv.org/abs/2210.14685), [Website](https://facebookresearch.github.io/latent-space-priors/), [Code](https://github.com/facebookresearch/latent-space-priors)) +- Hierarchical World Models as Visual Whole-Body Humanoid Controllers, by Nicklas Hansen et al. ([Paper](https://arxiv.org/abs/2405.18418), [Website](https://www.nicklashansen.com/rlpuppeteer/), [Code](https://github.com/nicklashansen/puppeteer)) +- Body Transformer: Leveraging Robot Embodiment for Policy Learning, by Carmelo Sferrazza et al. ([Paper](https://arxiv.org/abs/2408.06316), [Website](https://sferrazza.cc/bot_site/), [Code](https://github.com/carlosferrazza/BodyTransformer)) + ## Citation If you reference or use MoCapAct in your research, please cite: