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Fixed Action Patterns

Fixed Action Patterns

A fixed action pattern (FAP) is a specific, hard-wired sequence of behaviors that occurs in response to an external stimulus, called a sign stimulus. The behavior is “fixed” because it is essentially unchangeable—proceeding similarly across individuals of a species every time it occurs.

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Related Experiment Video

Updated: Sep 3, 2025

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

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Published on: July 5, 2024

APSNet: Toward Adaptive Point Sampling for Efficient 3D Action Recognition.

Jiaheng Liu, Jinyang Guo, Dong Xu

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society

|July 28, 2022

Summary

This summary is machine-generated.

Deploying 3D action recognition in real-world settings is challenging. Our adaptive point sampling network (APSNet) balances accuracy and efficiency by optimizing point cloud resolutions for 3D action recognition tasks.

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Area of Science:

Computer Vision
Machine Learning
Artificial Intelligence

Background:

Real-world deployment of 3D action recognition methods remains a significant challenge.
Existing methods often struggle to balance accuracy with computational efficiency.

Purpose of the Study:

To investigate the accuracy-efficiency trade-off in 3D action recognition.
To propose an efficient and effective network for 3D action recognition.

Main Methods:

Introduced a simple and efficient backbone network for extracting geometry and motion representations from raw point cloud videos.
Developed the Adaptive Point Sampling Network (APSNet), an end-to-end optimized network.
APSNet adaptively determines optimal point cloud resolutions per frame pair under computational constraints.

Main Results:

APSNet effectively achieves a favorable accuracy-efficiency trade-off for 3D action recognition.
Comprehensive experiments on benchmark datasets validate the proposed method's effectiveness and efficiency.

Conclusions:

The proposed APSNet offers a practical solution for deploying 3D action recognition in real-world scenarios.
Adaptive point sampling is a viable strategy for optimizing 3D action recognition performance and resource utilization.