The authors assembled 139 multi-camera scenes comprising 1,799 synchronized 1080p camera streams from warehouse-dominated indoor settings, alongside hospitals, retail venues and related spaces.
Benchmark tests multi-camera 3D tracking across synthetic and real spaces
The dataset combines synchronized indoor video, dense 3D annotations, appearance-transferred imagery and held-out real-world evaluation.
Big Tech
Yuxing Wang · Yizhou Wang · Anqi Li · Shuo Wang · Sameer Satish Pusegaonkar · Haoquan Liang · +10 more
NVIDIA · Santa Clara University
Research Digest··3 min read
Wang and colleagues present Physical AI Smart Spaces, a benchmark for tracking people, robots and industrial vehicles in 3D across networks of fixed cameras.
Why this paper
From NVIDIA and Santa Clara University
In one line
NVIDIA's Physical AI Smart Spaces benchmark provides 280+ hours of multi-camera 3D perception data for warehouses and smart spaces.
What we could check
- ·No code link found
- ·No weights link found
- ·No dataset link found
- ·No compute details found
- ✓Limitations stated by the authors (3 noted)
- ·No benchmark numbers found
Observed from the paper text and links we have. Absence here means we did not find it, not that it does not exist.
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