TODO before making this repo public: confirm permission from the CMU Panoptic Studio organisers. Until then the repo must stay gated and private. See LICENSE_NOTICE.md.

Per-person instance segmentation masks for the CMU Panoptic Studio dataset, generated with SAM 3.1 (facebook/sam3.1 @ daa63191845a41281374e725f4c9e51c7a824460) and aligned to the dataset's own 3D skeletons: masks and pose share the same person id across all five VoxelPose HD cameras (3, 6, 12, 13, 23) and all frames.

These are model-generated pseudo-labels, not human annotations. Every published frame carries automated QA metrics (index.parquet); read the numbers below before trusting the masks for your use case.

This repo contains no CMU pixels -- masks, metadata and code only. Videos must be obtained directly from CMU under CMU's terms: run scripts/download_videos.py.

Layout

MANIFEST.json                        # full provenance: checkpoints, config, offsets, checksums
availability.json                    # probe results for all Tier A sequences
index.parquet                        # frame QA, person ids, Parquet row locators
masks/<seq>/hd_<cam>/part-*.parquet  # row-grouped per-frame COCO RLE instances
masks/<seq>/calib_subset.json        # the 5 HD cameras, verbatim from CMU calibration
scripts/download_videos.py           # fetch the source videos from CMU into a local cache
scripts/loader.py                    # yields (image, pose3d, instances) joined on person id
LICENSE_NOTICE.md

For shuffled PyTorch training, use CMUPanopticDataset from scripts/loader.py. It returns temporal RGB, padded pose-aligned masks, raw COCO19 pose, and forward joint velocity. Source videos and poses must first be downloaded with the included script. TorchCodec performs one exact batched indexed decode per sample.

Each Parquet row is one frame: person_id is the Panoptic id (identical in every camera); negative ids are text-detector instances with no 3D counterpart (no_3d_gt flag) -- real people outside the capture volume, not noise. rle=null means the person is reconstructed in 3D but not visible in this view. depth_proxy is camera-to-person distance in cm, giving free occlusion ordering.

Method

SAM 3.1's video predictor runs with a person text prompt in chunks of 600 frames with 10-frame overlaps; tracks are stitched across chunk seams by mask IoU (SAM ids are session-local). Panoptic person ids are then assigned by fitting whole trajectories of projected 3D joints against the tracked masks, with depth-weighted disambiguation for contested masks. The video/pose frame offset is resolved empirically per sequence (see MANIFEST.json), not assumed.

Coverage

Tier A of the corpus: 65 probe-verified sequences with HD pose, of which the following are currently packaged:

sequence	category	cameras	frames per camera
160224_haggling1	haggling	5	hd_12: 8716, hd_13: 8716, hd_23: 8716, hd_03: 8716, hd_06: 8716
160226_haggling1	haggling	5	hd_12: 11465, hd_13: 11465, hd_23: 11465, hd_03: 11465, hd_06: 11465
160422_haggling1	haggling	5	hd_12: 13580, hd_13: 13580, hd_23: 13580, hd_03: 13580, hd_06: 13580
160422_ultimatum1	ultimatum	5	hd_12: 26794, hd_13: 26794, hd_23: 26794, hd_03: 26794, hd_06: 26794
160906_band2	musical_instruments	5	hd_12: 7362, hd_13: 7362, hd_23: 7362, hd_03: 7362, hd_06: 7362
160906_ian1	toddler	5	hd_12: 2847, hd_13: 2847, hd_23: 2847, hd_03: 2847, hd_06: 2847
160906_ian3	toddler	5	hd_12: 7368, hd_13: 7368, hd_23: 7368, hd_03: 7368, hd_06: 7368
160906_ian5	toddler	5	hd_12: 2872, hd_13: 2872, hd_23: 2872, hd_03: 2872, hd_06: 2872
160906_pizza1	special_events	5	hd_12: 6582, hd_13: 6582, hd_23: 6582, hd_03: 6582, hd_06: 6582
161029_build1	special_events	5	hd_12: 8860, hd_13: 8860, hd_23: 8860, hd_03: 8860, hd_06: 8860
161029_car1	special_events	5	hd_12: 3525, hd_13: 3525, hd_23: 3525, hd_03: 3525, hd_06: 3525
161029_piano1	musical_instruments	5	hd_12: 8920, hd_13: 8920, hd_23: 8920, hd_03: 8920, hd_06: 8920
161029_tools1	special_events	5	hd_12: 5470, hd_13: 5470, hd_23: 5470, hd_03: 5470, hd_06: 5470
161202_haggling1	haggling	5	hd_12: 10850, hd_13: 10850, hd_23: 10850, hd_03: 10850, hd_06: 10850
170221_haggling_b1	haggling	5	hd_12: 14086, hd_13: 14086, hd_23: 14086, hd_03: 14086, hd_06: 14086
170221_haggling_b2	haggling	5	hd_12: 14266, hd_13: 14266, hd_23: 14266, hd_03: 14266, hd_06: 14266
170221_haggling_b3	haggling	5	hd_12: 14914, hd_13: 14914, hd_23: 14914, hd_03: 14914, hd_06: 14914
170221_haggling_m1	haggling	5	hd_12: 14626, hd_13: 14626, hd_23: 14626, hd_03: 14626, hd_06: 14626
170221_haggling_m2	haggling	5	hd_12: 14597, hd_13: 14597, hd_23: 14597, hd_03: 14597, hd_06: 14597
170221_haggling_m3	haggling	5	hd_12: 7074, hd_13: 7074, hd_23: 7074, hd_03: 7074, hd_06: 7074
170224_haggling_a2	haggling	5	hd_12: 19181, hd_13: 19181, hd_23: 19181, hd_03: 19181, hd_06: 19181
170224_haggling_a3	haggling	5	hd_12: 18132, hd_13: 18132, hd_23: 18132, hd_03: 18132, hd_06: 18132
170224_haggling_b1	haggling	5	hd_12: 19481, hd_13: 19481, hd_23: 19481, hd_03: 19481, hd_06: 19481
170224_haggling_b2	haggling	5	hd_12: 19181, hd_13: 19181, hd_23: 19181, hd_03: 19181, hd_06: 19181
170224_haggling_b3	haggling	5	hd_12: 18366, hd_13: 18366, hd_23: 18366, hd_03: 18366, hd_06: 18366
170228_haggling_a1	haggling	5	hd_12: 19181, hd_13: 19181, hd_23: 19181, hd_03: 19181, hd_06: 19181
170228_haggling_a2	haggling	5	hd_12: 18881, hd_13: 18881, hd_23: 18881, hd_03: 18881, hd_06: 18881
170228_haggling_a3	haggling	5	hd_12: 17443, hd_13: 17443, hd_23: 17443, hd_03: 17443, hd_06: 17443
170228_haggling_b1	haggling	5	hd_12: 23707, hd_13: 23707, hd_23: 23707, hd_03: 23707, hd_06: 23707
170228_haggling_b2	haggling	5	hd_12: 24037, hd_13: 24037, hd_23: 24037, hd_03: 24037, hd_06: 24037
170228_haggling_b3	haggling	5	hd_12: 21160, hd_13: 21160, hd_23: 21160, hd_03: 21160, hd_06: 21160
170307_dance5	dance	5	hd_12: 11617, hd_13: 11617, hd_23: 11617, hd_03: 11617, hd_06: 11617
170404_haggling_a1	haggling	5	hd_12: 9471, hd_13: 9471, hd_23: 9471, hd_03: 9471, hd_06: 9471
170404_haggling_a2	haggling	5	hd_12: 9675, hd_13: 9675, hd_23: 9675, hd_03: 9675, hd_06: 9675
170404_haggling_a3	haggling	5	hd_12: 11863, hd_13: 11863, hd_23: 11863, hd_03: 11863, hd_06: 11863
170404_haggling_b1	haggling	5	hd_12: 19062, hd_13: 19062, hd_23: 19062, hd_03: 19062, hd_06: 19062
170404_haggling_b2	haggling	5	hd_12: 19277, hd_13: 19277, hd_23: 19277, hd_03: 19277, hd_06: 19277
170404_haggling_b3	haggling	5	hd_12: 18558, hd_13: 18558, hd_23: 18558, hd_03: 18558, hd_06: 18558
170407_haggling_a1	haggling	5	hd_12: 14087, hd_13: 14087, hd_23: 14087, hd_03: 14087, hd_06: 14087
170407_haggling_a2	haggling	5	hd_12: 13847, hd_13: 13847, hd_23: 13847, hd_03: 13847, hd_06: 13847
170407_haggling_a3	haggling	5	hd_12: 12768, hd_13: 12768, hd_23: 12768, hd_03: 12768, hd_06: 12768
170407_haggling_b1	haggling	5	hd_12: 19122, hd_13: 19122, hd_23: 19122, hd_03: 19122, hd_06: 19122
170407_haggling_b2	haggling	5	hd_12: 18882, hd_13: 18882, hd_23: 18882, hd_03: 18882, hd_06: 18882
170407_haggling_b3	haggling	5	hd_12: 16364, hd_13: 16364, hd_23: 16364, hd_03: 16364, hd_06: 16364
170407_office2	special_events	5	hd_12: 5216, hd_13: 5216, hd_23: 5216, hd_03: 5216, hd_06: 5216
170915_office1	special_events	5	hd_12: 5378, hd_13: 5378, hd_23: 5378, hd_03: 5378, hd_06: 5378
170915_toddler5	toddler	5	hd_12: 3574, hd_13: 3574, hd_23: 3574, hd_03: 3574, hd_06: 3574
171026_cello3	musical_instruments	5	hd_12: 1728, hd_13: 1728, hd_23: 1728, hd_03: 1728, hd_06: 1728
171026_pose1	range_of_motion	5	hd_12: 22466, hd_13: 22466, hd_23: 22466, hd_03: 22466, hd_06: 22466
171026_pose2	range_of_motion	5	hd_12: 14974, hd_13: 14974, hd_23: 14974, hd_03: 14974, hd_06: 14974
171026_pose3	range_of_motion	5	hd_12: 7181, hd_13: 7181, hd_23: 7181, hd_03: 7181, hd_06: 7181
171204_pose1	range_of_motion	5	hd_12: 27561, hd_13: 27561, hd_23: 27561, hd_03: 27561, hd_06: 27561
171204_pose2	range_of_motion	5	hd_12: 37751, hd_13: 37751, hd_23: 37751, hd_03: 37751, hd_06: 37751
171204_pose3	range_of_motion	5	hd_12: 8920, hd_13: 8920, hd_23: 8920, hd_03: 8920, hd_06: 8920
171204_pose4	range_of_motion	5	hd_12: 31397, hd_13: 31397, hd_23: 31397, hd_03: 31397, hd_06: 31397
171204_pose5	range_of_motion	5	hd_12: 26902, hd_13: 26902, hd_23: 26902, hd_03: 26902, hd_06: 26902
171204_pose6	range_of_motion	5	hd_12: 22886, hd_13: 22886, hd_23: 22886, hd_03: 22886, hd_06: 22886

Excluded sequences and why:

160906_band3: known data corruption; dropped by TEMPO and prior work
170224_haggling_a1: pose coverage 0.00% below 90% threshold (0 pose frames vs ~21600 video frames for 12.0 min)

QA (automated, per activity category)

Joint containment = fraction of projected 3D joints landing inside their own person's mask. Temporal IoU = frame-to-frame mask IoU per track. Hull IoU = reprojection IoU of the visual hull carved from the five views. Full per-frame values are in index.parquet.

category	cameras	frames	masks	containment	temporal IoU	hull IoU	id switches	count jumps
dance	5	58085	81255	0.998	0.907	0.848	0	0
haggling	165	2629500	6663672	0.953	0.945	0.729	412	1425
musical_instruments	15	90050	188758	0.889	0.974	0.723	3	7
range_of_motion	45	1000190	1209746	0.998	0.961	0.774	15	23
special_events	30	175155	375902	0.902	0.951	0.707	3	9
toddler	20	83305	175198	0.916	0.931	0.719	3	19
ultimatum	5	133970	612248	0.914	0.946	0.598	29	41

Known limitations

Pseudo-labels: no human ever verified an individual mask. Raw containment dips on steep views are dominated by occlusion (occlusion-adjusted containment is reported in per-sequence QA), but genuine mask errors exist.
Negative-id bystander tracks fragment across chunk seams; their ids are not stable over time. Subject ids (>= 0) are.
Source videos contain defects (e.g. corrupt GOPs decoding to solid green); frames flagged count_jump in index.parquet deserve suspicion.
Coverage is limited to the Tier A sequences listed above.

Citation

If you use this data, cite the CMU Panoptic Studio papers (required by CMU) and SAM 3: Joo et al., Panoptic Studio: A Massively Multiview System for Social Motion Capture, ICCV 2015; Joo et al., TPAMI 2017; Simon et al., Hand Keypoint Detection in Single Images using Multiview Bootstrapping, CVPR 2017. Full BibTeX in LICENSE_NOTICE.md.

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