From 8a60e32ca015ba0ee25864e8aa438908fc8ce451 Mon Sep 17 00:00:00 2001 From: Zhenqiang Li Date: Wed, 22 Jun 2022 23:48:14 +0900 Subject: [PATCH] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index e3f72fc..606d92e 100644 --- a/README.md +++ b/README.md @@ -1,4 +1,4 @@ -# Video Visual Explanations +# Towards Visually Explaining Video Understanding Networks With Perturbation This is a PyTorch demo implemented several visualization methods for video classification networks. The target is to provide a toolkit (as [TorchRay](https://github.com/facebookresearch/TorchRay) to image) to interprete commonly utilized video classfication networks, such as I3D, R(2+1)D, TSM et al., which is also called *attribution* task, namely the problem of determining which part of the input video is responsible for the value computed by a neural network. More information can also be referenced in our paper [Towards Visually Explaining Video Understanding Networks With Perturbation](https://openaccess.thecvf.com/content/WACV2021/papers/Li_Towards_Visually_Explaining_Video_Understanding_Networks_With_Perturbation_WACV_2021_paper.pdf).