sam3
Datasets
All datasets matching “sam3”sam3d-flat-20260329-022951ff4d-sam3d-prep
ff4d-sam3d prepped training data (motion324 + syn4d)
STATUS: upload in progress (started 2026-09-07 ~00:20 CDT, ETA ~04:00 CDT).
Files appear a few GB at a time, stream by stream. pointmaps is the largest stream and lands
last for each root. Check the file list for what is already complete; a __NNN.tar that is
present is complete (each is committed only after a successful upload).
Prepped training samples for ff4d-sam3d — video-to-4D on the SAM-3D Objects backbone. Each sample… See the full description on the dataset page: https://huggingface.co/datasets/Testing12321111/ff4d-sam3d-prep.sam3-sgv4-experiment-artifacts
SAM3 SG-v4 experiment artifacts
Private backup of the experiment-specific artifacts under
sam3_sgv4_fullcoverage_20260731.
The original COCO/RefCOCO and ReasonSeg datasets remain in
xuzishan/sam3-datasets. This repository is for generated material that is
not recoverable from those original datasets:
RefCOCO, RefCOCO+, and RefCOCOg four-rollout training trajectories;
thinking histories, trajectory JSONL, predictions, masks, and GT snapshots;
ReasonSeg generated outputs;… See the full description on the dataset page: https://huggingface.co/datasets/xuzishan/sam3-sgv4-experiment-artifacts.libero_10_sam3_visual_prompts
LIBERO-10 SAM3 Visual Prompts
This dataset contains SAM3-generated visual prompts for successful episodes from
fracapuano/libero_10.
It does not contain a trained policy model. The files are per-episode visual
prompt annotations aligned to the original LeRobot episode frames.
Contents
libero_10/chunk-000/episode_*.npz: visual prompt annotations.
manifest_success.jsonl: one row per saved episode with task metadata and hit rates.
videos/episode_*_sam3_vp.mp4: rendered… See the full description on the dataset page: https://huggingface.co/datasets/TechieMoon/libero_10_sam3_visual_prompts.gpic-bcc-sam3-qwen38-27b
GPIC Bidirectional Concept Correspondence Data
This release was generated by ConCor Training Data Generation. Each training example connects a text mask—a set of caption character spans—to an image mask made from one or more segmented instances. Disjoint co-referring spans can therefore share the same correspondence.
The three training configs intentionally match the caption-row format used by UWGZQ/ConCor-1-Data. Our richer pipeline records and complete per-image dispositions… See the full description on the dataset page: https://huggingface.co/datasets/suryadv/gpic-bcc-sam3-qwen38-27b.ff4d-sam3d-prep
ff4d-sam3d prepped training data (motion324 + syn4d)
STATUS: upload complete (2026-09-07 23:01 UTC). Check COMPLETE.txt for the per-stream entry counts.
Files appear a few GB at a time, stream by stream. pointmaps is the largest stream and lands
last for each root. Check the file list for what is already complete; a __NNN.tar that is
present is complete (each is committed only after a successful upload).
Prepped training samples for ff4d-sam3d — video-to-4D on the SAM-3D… See the full description on the dataset page: https://huggingface.co/datasets/ncc2/ff4d-sam3d-prep.