ubr-physical-ai2026cc-by-4.0
Cosmos3 image-to-video: subject survival on synthetic rescue scenes
26 generated video clips from NVIDIA Cosmos3 models conditioned on synthetic Isaac Sim frames, with per-frame detection scores measuring whether image-to-video generation maintains subject presence across frames. Published as a negative result demonstrating that image-conditioned generation fails to hold subjects in place without per-frame control signals.
Downloads0
Episodes26
Why This Matters for Physical AI
Demonstrates fundamental limitations of image-conditioned video generation for maintaining object persistence in synthetic scenes, informing design choices for perception models in search-and-rescue robotics applications.
Technical Profile
- Modalities
- rgbvideo
- Environment
- simulation
- Task Types
- search-and-rescue
- Episodes
- 26
- Data Format
- mp4
- Annotation Types
- bounding_boxesdetection_labels
- License
- cc-by-4.0
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