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arXiv AI By Stefanos Gkikas, Christian Arzate Cruz, Eric Nichols, Giorgos Giannakakis, Randy Gomez

UNWIND: Any-Length Facial Video for Stress Detection without Temporal Windowing

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UNWIND is a facial‑video framework that detects stress by treating an entire recording as a single input, avoiding the need for temporal windowing or segmentation. It folds the video’s temporal dimension into the channel dimension of a 2‑D spatial representation and processes it with an asymmetric‑attention architecture. Experiments on a 58‑subject stress dataset show that using all 3,600 frames (stride τ = 1) yields a 69.73 % accuracy, comparable to the best 70.02 % accuracy at τ = 15, while computational cost varies from 12.48 to 348.78 GFLOPs.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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