arXiv Computer Vision September 3, 2026 By Seongro Yoon, Donghyeon Cho, Jinsun Park, Fran\c{c}ois Br\'emond

Reweighting Framewise Attention in Video Transformers for Facial Expression Understanding

Read the original on arXiv Computer Vision →

The paper introduces MiRA, a plug‑in framework that reweights framewise attention in Vision Transformer video models to better capture subtle facial dynamics for expression recognition. MiRA computes frame‑level confidence and intra‑frame concentration from self‑attention maps, redistributing attention toward localized facial cues without adding trainable parameters. Two modes—an exact post‑softmax redistribution and a lightweight flashLite pre‑softmax approximation—are proposed, and experiments on facial expression recognition benchmarks show consistent gains over strong ViT baselines.

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 Computer Vision.

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