datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
SpatialEdit-500K
SpatialEdit-500K
SpatialEdit-500K is a synthetic training dataset for fine-grained image spatial editing. It is built for learning geometry-aware edits such as object moving, object rotation, and camera viewpoint change.
The dataset was introduced in the paper SpatialEdit: Benchmarking Fine-Grained Image Spatial Editing. It is generated with a controllable rendering pipeline to provide structured spatial transformations at scale.
Project Resources
GitHub Repository:… See the full description on the dataset page: https://huggingface.co/datasets/EasonXiao-888/SpatialEdit-500K.libero_spatial_imageHoliSpatial-QA-2MSpatialReasonerTrainScanNetPPSpatialQA-ESpatialQA-E is a robot manipulation dataset focusing on spatial relationship understanding.
Paper:
https://arxiv.org/abs/2406.13642
GitHub repo:
https://github.com/BAAI-DCAI/SpatialBot
SpatialBot-general QA, a VLM with precise depth understanding:
https://huggingface.co/RussRobin/SpatialBot
SpatialBench, the spatial understanding benchmark in general QA:
https://huggingface.co/datasets/RussRobin/SpatialBench
spatialvid_frameslibero_1_spatialSpatialQAspatialMulti-SpatialMLLM
