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Tags: Machine learning
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The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

The repository provides code for running inference and finetuning with the Meta Segment Anything Model 3 (SAM 3), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

The repository provides code for running inference with the Meta Segment Anything Audio Model (SAM-Audio), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

The repository provides code for running inference with the SAM 3D Body Model (3DB), links for downloading the trained model checkpoints and datasets, and example notebooks that show how to use the model.

WeVisOne-VL is a powerful VLM by the WeChat Vision Team at Tencent, unifying object-level and pixel-level perception from points and boxes to masks and alpha mattes.

A 3D vision library from 2D keypoints: monocular and stereo 3D detection for humans, social distancing, and body orientation.

  • 3d-object-detection
  • 3d-detection
  • 3d-deep-learning
  • pytorch

Whole-body motion tracking for the Unitree G1 in under 3 minutes on average on one GPU: return 0.82 with 0/40 clips failed, held from 2.74 min (mean of 15 seeds, range 2.21-3.61, fine checkpoints), 11.87 it/s (world model + Muon + overlapped CUDA streams, mjlab)

  • humanoid
  • robot-learning
  • supermimic
  • world-model