UniSim
UC Berkeley / research
Interactive real-world simulator research that models how visual scenes change under actions and interaction.
Interactive scene prediction
Useful reference for OpenBot Synth because generated replay should stay anchored to real interaction traces.
A model hub link is a declaration. Files, loadability, evaluation, and deployment are scored separately.
Model decision scorecard
Use-case scores and evidence confidence are separate; Unknown is not treated as failure.
Code, weights, and checkpoints
UnknownArtifact availability is unknown.
Loading and training reproducibility
UnknownNo verified loading configuration is available.
Training data requirements
UsefulRequired signal categories are declared; exact tensor and action interfaces still need verification.
Evaluation evidence
UsefulEvaluation focus is declared, but metrics are not independently verified.
Deployment readiness
UnknownHardware, latency, dependencies, and runtime loading are not yet verified.
Artifact facts and provenance
No metadata-verified artifact facts yet. Source links remain declarations only.
Loop signal demand
Signals this model family needs for training, evaluation, or failure mining.
Observation / ego video
observation · camera pose · Video traces with action or interaction conditioning
Language intent / task phase
Needs task intent, instructions, keysteps, or phase labels to connect behavior to goals.
Action / robot state
actions · Video traces with action or interaction conditioning
Future state / dynamics
future state · Temporal consistency signals and scene geometry · Evaluation setups that connect predicted rollouts to downstream control or planning · Interactive scene prediction
Feedback / correction / failure
Evaluation setups that connect predicted rollouts to downstream control or planning
Sim-real / embodiment metadata
camera pose · sim-real
Evaluation focus
- Interactive scene prediction
- Long-horizon rollout consistency
- Whether imagined futures support planning or policy debugging
Missing critical loop signals
Core signal demands are represented. Check quality, alignment, and access constraints.
Related catalog datasets
Ego-1K
Multiview egocentric scene reconstruction
Exact action dimensions, control frequency, normalization, and camera mapping require interface verification.
Xperience-10M
Multimodal human experience for embodied AI
Exact action dimensions, control frequency, normalization, and camera mapping require interface verification.
Ego-Realm
Small egocentric sample set for manipulation domains
Exact action dimensions, control frequency, normalization, and camera mapping require interface verification.
OpenBot notes
- Useful reference for OpenBot Synth because generated replay should stay anchored to real interaction traces.
- Highlights the need for future-state and sim-real tags in datasets.