Palm: Predicting Actions through Language Models @ Ego4D Long-Term
  Action Anticipation Challenge 2023
Daoji Huang Otmar Hilliges Luc Van Gool Xi Wang
We present Palm, a solution to the Long-Term Action Anticipation (LTA) task
utilizing vision-language and large language models. Given an input video with
annotated action periods, the LTA task aims to predict possible future actions.
We hypothesize that an optimal solution should capture the interdependency
between past and future actions, and be able to infer future actions based on
the structure and dependency encoded in the past actions. Large language models
have demonstrated remarkable commonsense-based reasoning ability. Inspired by
that, Palm chains an image captioning model and a large language model. It
predicts future actions based on frame descriptions and action labels extracted
from the input videos. Our method outperforms other participants in the EGO4D
LTA challenge and achieves the best performance in terms of action prediction.
Our code is available at https://github.com/DanDoge/Palm