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Found 3 papers, 3 papers with code
Just Add $π$! Pose Induced Video Transformers for Understanding Activities of Daily Living
To facilitate the adoption of video transformers for ADL, we hypothesize that the augmentation of RGB with human pose information, known for its sensitivity to fine-grained motion and multiple viewpoints, is essential.
Ranked #1 on
Action Classification
on Toyota Smarthome dataset
(using extra training data)
Limited Data, Unlimited Potential: A Study on ViTs Augmented by Masked Autoencoders
We explore the appropriate SSL tasks that can be optimized alongside the primary task, the training schemes for these tasks, and the data scale at which they can be most effective.
Seeing the Pose in the Pixels: Learning Pose-Aware Representations in Vision Transformers
Both PAAT and PAAB surpass their respective backbone Transformers by up to 9. 8% in real-world action recognition and 21. 8% in multi-view robotic video alignment.
