TAVIS: A Benchmark for Egocentric Active Vision and Anticipatory Gaze in Imitation Learning
Active vision -- where a policy controls its own gaze during manipulation -- has emerged as a key capability for imitation learning, with multiple independent systems demonstrating its benefits in the past year. Yet there is no shared benchmark to compare approaches or quantify what active vision contributes, on which task types, and under what conditions. We introduce TAVIS, evaluation infrastructure for active-vision imitation learning, with two complementary task suites -- TAVIS-Head (5 tasks, global search via pan/tilt necks) and TAVIS-Hands (3 tasks, local occlusion via wrist cameras) -- on two humanoid torso embodiments (GR1T2, Reachy2), built on IsaacLab. TAVIS provides three evalu...
| Authors | Giacomo Spigler |
|---|---|
| Primary category | cs.RO |
| Published | 8 May 2026 |
| Last updated at source | 6 October 2026 |
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