Action Detection using MDETR

This repository contains code and link to run Atomic Visual Actions (AVA) into Modulated Detection Transformer (MDETR) for action recognition.

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Introduction

During recent years transformers architectures have been growing in popularity. Modulated Detection Transformer (MDETR) is an end-to-end multi-modal understanding model that performs tasks such as phase grounding, referring expression comprehension, referring expression segmentation, and visual question answering. One remarkable aspect of the model is the capacity to infer over classes that it was not previously trained for. In this work we explore the use of MDETR in a new task, action detection, without any previous training. We obtain quantitative results using the Atomic Visual Actions dataset. Although the model does not report the best performance in the task, we believe that it is an interesting fiding. We show that it is possible to use a multi-modal model to tackle a task that it was not designed for. Finally, we believe that this line of research may lead into the generalization of MDETR in additional downstream tasks.

Examples

Here can be seen some images processed with MDETR, and plotting to see the rectangle around object detected. Also, you can the confidence, which is a metric that MDETR provides, to know how sure it is about the result get. In our code, many detections are discarded because confidence is not high enough. You can change that modifying "CONFIDENCE" constante in the code.

Success results

Images	Images

Failure results

As it can be seem, in some cases MDETR recognized succesfully actions, but in others, it failed. That was expected, because model was not trained specifically for this dataset, images in AVA are difficult to process and MDETR was not thought to work with actions. All this factors causes that model fails to recognized some situations in images.

Results

After running validation dataset of AVA, we get some results. There were actions easily recognized, and others that not.

	Pascal Boxes	Category Results
Category	AP@0.5IOU	Category	AP@0.5IOU
Sleep	0.0019	answer phone	0.0
Sit	0.0016	kiss (a person)	0.0
Stand Up	0.0011	throw	0.0
Handshake	0.0005	touch (an object)	0.0
Dance	0.0005	touch (an object)	0.0