TrAction: Action Recognition with Sparse Trajectories 事件

TrAction: Action Recognition with Sparse Trajectories arXiv:2606.03490v1 Announce Type: new Abstract: Modern action recognition models operate on memory- and compute-intensive dense RGB video volumes and frequently exploit appearance and background shortcuts, for example, predicting actions from objects or scenes instead of characteristic motion. We investigate an efficient alternative input modality that is largely free of such biases by construction: sparse point trajectories. To this end, we