hip
Datasets
All datasets matching “hip”HiPHI
HiPHI: A large-scale benchmark for high-precision human motion and object interaction.
Project page: https://noitom-robotics.github.io/hiphi/
Online viewer: https://hiphi-viewer.modalitynet.com/
Paper: http://arxiv.org/abs/2608.16222
GitHub: https://github.com/noitom-robotics/hiphi/
HiPHI is an optical motion-capture dataset for humanoid learning and
whole-body motion modeling. It provides standardized BVH motion and, for
human-object interaction… See the full description on the dataset page: https://huggingface.co/datasets/noitomrobotics/HiPHI.HippoCamp
HippoCamp: Benchmarking Contextual Agents on Personal Computers
📖 Paper |
🏠 Project Page |
🛠️ GitHub |
🤗 Dataset |
🎬 Demo
Overview
HippoCamp is a benchmark for evaluating contextual agents in realistic, device-resident personal computing environments. Unlike agent benchmarks centered on web interaction, tool use, or generic software automation, HippoCamp focuses on multimodal file management over large personal file systems: agents must… See the full description on the dataset page: https://huggingface.co/datasets/MMMem-org/HippoCamp.hippoFakeParts
FakeParts: A New Family of AI-Generated DeepFakes
Abstract
We introduce FakeParts, a new class of deepfakes characterized by subtle, localized manipulations to specific spatial regions or temporal segments of otherwise authentic videos. Unlike fully synthetic content, these partial manipulations—ranging from altered facial expressions to object substitutions and background modifications—blend seamlessly with real elements, making them particularly deceptive… See the full description on the dataset page: https://huggingface.co/datasets/hi-paris/FakeParts.HippoRAG_2
HippoRAG 2 is a powerful memory framework for LLMs that enhances their ability to recognize and utilize connections in new knowledge—mirroring a key function of human long-term memory.HIP-UMA-OMol25
HIP-UMA-OMol25
Snapshot of completed UMA-S-1.2 (uma-s-1p2) predictions on a uniform
sample of OMol-1 train geometries, using the omol task.
This snapshot contains only validated, complete HDF5 shards. Checkpoint
files (*.partial.h5) are intentionally excluded.
Current snapshot (2026-08-21): 10846 complete shards, about 25 GB,
4.3 million samples. The full 10M campaign is still running (41911 shards planned).
Shard files are grouped to stay under Hugging Face's 10… See the full description on the dataset page: https://huggingface.co/datasets/andreasburger/HIP-UMA-OMol25.
