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Current methods struggle to understand human behavior in industrial settings, as evidenced by the challenging ENIGMA-360 dataset of synchronized ego-exo videos.
Differentiable Viterbi decoding unlocks state-of-the-art procedural planning with an order of magnitude fewer parameters than LLM-based approaches.
By modeling environment affordances and interaction hotspots, STAformer++ boosts short-term object interaction anticipation by up to 31 percentage points on EPIC-Kitchens.
