datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
human-motion-tracking-deeplabcutThis dataset is used to adapt DeepLabCut for Human motion tracking.
Structure of the dataset
videos contains 100+ videos of 4 candidates recorded during a game of darts.
labeled-data contains labels on the corresponding frames of the videos. These labels are used to adapt DeepLabCut for human motion tracking. Under labeled-data there are 2 folders for every video.
video_name has all the relevant frames extracted from the video, xy coordinates of the labels in the csv file and the… See the full description on the dataset page: https://huggingface.co/datasets/GT-Neuronext/human-motion-tracking-deeplabcut.UniSafeBenchneuronav-dp-r14-unity
NeuroNav R14 Unity player and eight maps
Linux x86_64 Unity player tree used for real R14 navigation rollout, plus the
eight fixed evaluation map PNGs. Crash dumps and desktop metadata are excluded;
runtime files are hash listed in manifest.json.
STELAR-topo_vision_reasoning_SFT_50k
Stellar-Neuron/STELAR-topo_vision_reasoning_SFT_50k
[Paper] [HF Collection] [Project Page]
The dataset was released as part of STELAR-VISION: Self-Topology-Aware Efficient Learning for Aligned Reasoning in Vision. STELAR is a more accurate, faster and greener intelligent system for Vision Language Reasoning.
Contact: chenli4@andrew.cmu.edu
Dataset Summary
This dataset was created by STELAR TopoAug from two base datasets: Math-V and VLM_S2H. Each question includes… See the full description on the dataset page: https://huggingface.co/datasets/Stellar-Neuron/STELAR-topo_vision_reasoning_SFT_50k.STELAR-topo_vision_reasoning_preference_123k
Stellar-Neuron/STELAR-topo_vision_reasoning_preference_123k
[Paper] [HF Collection] [Project Page]
The dataset was released as part of STELAR-VISION: Self-Topology-Aware Efficient Learning for Aligned Reasoning in Vision. STELAR is a more accurate, faster and greener intelligent system for Vision Language Reasoning.
Contact: chenli4@andrew.cmu.edu
Dataset Summary
This dataset was created by STELAR TopoAug from two base datasets: Math-V and VLM_S2H.
Each question includes… See the full description on the dataset page: https://huggingface.co/datasets/Stellar-Neuron/STELAR-topo_vision_reasoning_preference_123k.devin-neuron-artworkcrop-disease-20kSTELAR-topo_vision_reasoning_100k
Stellar-Neuron/STELAR-topo_vision_reasoning_100k
[Paper] [HF Collection] [Project Page]
The dataset was released as part of STELAR-VISION: Self-Topology-Aware Efficient Learning for Aligned Reasoning in Vision. STELAR is a more accurate, faster and greener intelligent system for Vision Language Reasoning.
Contact: chenli4@andrew.cmu.edu
Dataset Summary
This dataset was created by STELAR TopoAug from two base datasets: Math-V and VLM_S2H. Each question includes responses… See the full description on the dataset page: https://huggingface.co/datasets/Stellar-Neuron/STELAR-topo_vision_reasoning_100k.s2lcd
Sentinel-2 Land-cover Captioning Dataset
The Sentinel-2 Land-cover Captioning Dataset (S2LCD) is a newly proposed dataset specifically designed for deep learning research on remote sensing image captioning. It comprises 1533 image patches, each of size 224 × 224 pixels, derived from Sentinel-2 L2A images. The dataset ensures a diverse representation of land cover and land use types in temperate regions, including forests, mountains, agricultural lands, and urban areas, each one with… See the full description on the dataset page: https://huggingface.co/datasets/neuronelab/s2lcd.neuronsflickr8k
Dataset Card for "flickr8k"
More Information needed
neuron-spectra-classifierSofia_facelu.i-neuronpcbneuron-activation-demo