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Independent publisher

Gehao Zhang

gehaozhang

Models in Library3
Datasets in Library0
Models on Hugging Face3
Followers—

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This profile connects the 3 model and dataset records shown below to their upstream cards and sources. The library counts describe SAVRN's coverage, rather than this publisher's entire output.

Published tasks: Robotics.

Reported licenses: other. Open a record to review its specific license and conditions.

Compare model specifications, source dates, and hardware estimates on the individual records. Publisher identity verification is separate from a model's quality, deployment readiness, or suitability for your work.

Models

Model · Robotics

gam-wilddet3d

Gehao Zhang

The benchmark-independent weights of GAM (Grounded Action Model): the general WildDet3D detector (SAM3 backbone, text / click prompts, 2D + 3D box heads, depth head) and the universal span head that turns a task string into the object phrases to ground. They are the defaults of the LeRobot / real-robot line of the released code (configs/lerobotbimanual.yaml): a LeRobot dataset with a task string can be trained on without manual labelling, but these weights are not tuned to any particular scene — on a new robot / camera / object set the detector (and the span head) may need fine-tuning for reliable grounding. Resolution matters. WildDet3D's native input is about 1k pixels (images are…

Open weights other lerobot

Model · Robotics

gam-robotwin

Gehao Zhang

GAM (Grounded Action Model) grounds the objects named in the instruction with an open-vocabulary 3D detector (WildDet3D), turns each object into a 3D box, a point cloud and a handful of image tokens, and predicts action chunks with a flow-matching transformer. This repository holds everything the released code needs to run GAM on RoboTwin 2.0: the RoboTwin-tuned detector, one action expert per task and the precomputed training cache of every task. All files are referenced from configs/robotwin/.yaml and download on first use. The videos are evaluation rollouts of the released experts; the wireframes are the 3D boxes the policy was given at that step (predicted by the detector from the RGB…

Open weights other

Model · Robotics

gam-libero-pro

Gehao Zhang

GAM (Grounded Action Model) grounds the objects named in the instruction with an open-vocabulary 3D detector (WildDet3D), turns each object into a 3D box, a point cloud and a handful of image tokens, and predicts action chunks with a flow-matching transformer. This repository holds everything the released code needs to run GAM on LIBERO / LIBERO-PRO: the LIBERO-tuned detector, one policy for all four suites, its span head and the precomputed training cache. All files are referenced from configs/liberopro.yaml and download on first use; the LIBERO-PRO task files (bddl + initial states) are in The videos are evaluation rollouts of the released policy on LIBERO-PRO cells (suite /…

Open weights other