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Reka RIDM: game-trained motion labels for real-video world-model data

Released compact game-trained inverse-motion models, comparing optical-flow inputs with direct pixels and using filtered/resampled game controls to infer movement/camera labels for unlabeled videos.

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Released compact game-trained inverse-motion models, comparing optical-flow inputs with direct pixels and using filtered/resampled game controls to infer movement/camera labels for unlabeled videos.

Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.

Scientific scope

Inverse dynamics, RAFT optical flow, IMPALA and VPT-style encoders are inherited. Inferred game-key/camera labels on video are not measured robot joint torques or true causal motor commands. Real-video evaluations are small; some metrics lack run logs and are marked unconfirmed. The pixel model explicitly fails on real-world footage. Code/weights license does not license evaluation media or game data.

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English catalogue narrative

Reka RIDM: game-trained motion labels for real-video world-model data

Released compact game-trained inverse-motion models, comparing optical-flow inputs with direct pixels and using filtered/resampled game controls to infer movement/camera labels for unlabeled videos.

Scientific scope

Inverse dynamics, RAFT optical flow, IMPALA and VPT-style encoders are inherited. Inferred game-key/camera labels on video are not measured robot joint torques or true causal motor commands. Real-video evaluations are small; some metrics lack run logs and are marked unconfirmed. The pixel model explicitly fails on real-world footage. Code/weights license does not license evaluation media or game data.

People and systems

Original sources