From 576fd9f7c75e316fae895ffcb67df72d37b21508 Mon Sep 17 00:00:00 2001
From: freeneuro <923237475@qq.com>
Date: Thu, 9 Dec 2021 21:10:05 +0800
Subject: [PATCH] Update README.md

---
 README.md | 75 +++++++++++++++++++++++++++++++++++++------------------
 1 file changed, 51 insertions(+), 24 deletions(-)

diff --git a/README.md b/README.md
index 82e9c72..f428bb0 100644
--- a/README.md
+++ b/README.md
@@ -1,25 +1,36 @@
-## [AAAI 2022] FCA: Learning a 3D Full-coverage Vehicle Camouflage for Multi-view Physical Adversarial Attack
+# [AAAI 2022] FCA: Learning a 3D Full-coverage Vehicle Camouflage for Multi-view Physical Adversarial Attack
 
-### Overview
+## Overview
 This is the official implementation and case study of the Full-coverage Vehicle Camouflage(FCA) method proposed in our AAAI 2022 paper [FCA: Learning a 3D Full-coverage Vehicle Camouflage for Multi-view Physical Adversarial Attack](https://arxiv.org/abs/2109.07193). 
 
 Source code can be find in [here](https://github.com/idrl-lab/Full-coverage-camouflage-adversarial-attack/tree/gh-pages/src).
 
-### Cases of Digital Attack
+## Abstract
+Physical adversarial attacks in object detection have attracted increasing attention. However, most previous works focus on hiding the objects from the detector by generating an individual adversarial patch, which only covers the planar part of the vehicle’s surface and fails to attack the detector in physical scenarios for multi-view, long-distance and partially occluded objects. To bridge the gap between digital attacks and physical attacks, we exploit the full 3D vehicle surface to propose a robust Full-coverage Camouflage Attack (FCA) to fool detectors. Specifically, we first try rendering the non-planar
+camouflage texture over the full vehicle surface. To mimic the real-world environment conditions, we then introduce a transformation function to transfer the rendered camouflaged vehicle into a photo-realistic scenario. Finally, we design an efficient loss function to optimize the camouflage texture. Experiments show that the full-coverage camouflage attack can not only outperform state-of-the-art methods under various test cases but also generalize to different environments, vehicles, and object detectors.
 
+## Framework
+![image-20211209204327675](https://gitee.com/freeneuro/PigBed/raw/master/img/image-20211209204327675.png)
 
-#### Carmear distance is 3
+## Cases of Digital Attack
 
+### Multi-view AttackL: Carmear distance is 3
 
 <table frame=void>
+    <tr>
+      <td></td>
+      <td>Elevation 0</td>
+      <td>Elevation 30</td>
+      <td>Elevation 50</td>
+    </tr>
   <tr>
-    <td>before</td>
+    <td>Original</td>
     <td><center> <img src = 'https://github.com/winterwindwang/Full-coverage-camouflage-adversarial-attack/blob/gh-pages/assets/distance_3_elevation_0_ori_pred.gif?raw=true'/></center></td>
         <td><center> <img src = 'https://github.com/winterwindwang/Full-coverage-camouflage-adversarial-attack/blob/gh-pages/assets/distance_3_elevation_30_ori_pred.gif?raw=true'/></center></td>
     <td><center> <img src = 'https://github.com/winterwindwang/Full-coverage-camouflage-adversarial-attack/blob/gh-pages/assets/distance_3_elevation_50_ori_pred.gif?raw=true'/></center></td>
   </tr>
     <tr>
-    <td>after</td>
+    <td>FCA</td>
     <td><center><img src = 'https://github.com/winterwindwang/Full-coverage-camouflage-adversarial-attack/blob/gh-pages/assets/distance_3_elevation_0_adv_pred.gif?raw=true'/></center></td>
     <td><center><img src = 'https://github.com/winterwindwang/Full-coverage-camouflage-adversarial-attack/blob/gh-pages/assets/distance_3_elevation_30_adv_pred.gif?raw=true'/></center></td>    
     <td><center><img src = 'https://github.com/winterwindwang/Full-coverage-camouflage-adversarial-attack/blob/gh-pages/assets/distance_3_elevation_50_adv_pred.gif?raw=true'/></center></td>
@@ -27,42 +38,58 @@ Source code can be find in [here](https://github.com/idrl-lab/Full-coverage-camo
 </table>
 
 
-#### Carmear distance is 5  
+### Multi-view AttackL: Carmear distance is 5  
+
 <table border=0>
+    <tr>
+      <td></td>
+      <td>Elevation 20</td>
+      <td>Elevation 40</td>
+      <td>Elevation 50</td>
+    </tr>
    <tr>
-      <td>before</td>
+      <td>Original</td>
     <td><center> <img src = 'https://github.com/winterwindwang/Full-coverage-camouflage-adversarial-attack/blob/gh-pages/assets/distance_5_elevation_20_ori_pred.gif?raw=true'/></center></td>
-         <td><center> <img src = 'https://github.com/winterwindwang/Full-coverage-camouflage-adversarial-attack/blob/gh-pages/assets/distance_5_elevation_50_ori_pred.gif?raw=true'/></center></td>
+     <td><center> <img src = 'https://github.com/winterwindwang/Full-coverage-camouflage-adversarial-attack/blob/gh-pages/assets/distance_5_elevation_40_ori_pred.gif?raw=true'/></center></td>
+    <td><center> <img src = 'https://github.com/winterwindwang/Full-coverage-camouflage-adversarial-attack/blob/gh-pages/assets/distance_5_elevation_50_ori_pred.gif?raw=true'/></center></td>
   </tr>
     <tr>
-     <td>after</td>
+     <td>FCA</td>
     <td><center><img src = 'https://github.com/winterwindwang/Full-coverage-camouflage-adversarial-attack/blob/gh-pages/assets/distance_5_elevation_20_adv_pred.gif?raw=true'/></center></td>
+    <td><center><img src = 'https://github.com/winterwindwang/Full-coverage-camouflage-adversarial-attack/blob/gh-pages/assets/distance_5_elevation_40_adv_pred.gif?raw=true'/></center></td> 
     <td><center><img src = 'https://github.com/winterwindwang/Full-coverage-camouflage-adversarial-attack/blob/gh-pages/assets/distance_5_elevation_50_adv_pred.gif?raw=true'/></center></td>
   </tr>
 </table>
 
 
-#### Carmear distance is 10
+### Multi-view AttackL: Carmear distance is 10
+
 <table>
     <tr>
-      <td>before</td>
+      <td></td>
+      <td>Elevation 30</td>
+      <td>Elevation 40</td>
+      <td>Elevation 50</td>
+    </tr>
+    <tr>
+      <td>Original</td>
     <td><center> <img src = 'https://github.com/winterwindwang/Full-coverage-camouflage-adversarial-attack/blob/gh-pages/assets/distance_10_elevation_30_ori_pred.gif?raw=true'/></center></td>
+    <td><center> <img src = 'https://github.com/winterwindwang/Full-coverage-camouflage-adversarial-attack/blob/gh-pages/assets/distance_10_elevation_40_ori_pred.gif?raw=true'/></center></td>
     <td><center> <img src = 'https://github.com/winterwindwang/Full-coverage-camouflage-adversarial-attack/blob/gh-pages/assets/distance_10_elevation_50_ori_pred.gif?raw=true'/></center></td>
   </tr>
     <tr>
-    <td>after</td>
-<td><center><img src = 'https://github.com/winterwindwang/Full-coverage-camouflage-adversarial-attack/blob/gh-pages/assets/distance_10_elevation_30_adv_pred.gif?raw=true'/></center></td>
+    <td>FCA</td>
+    <td><center><img src = 'https://github.com/winterwindwang/Full-coverage-camouflage-adversarial-attack/blob/gh-pages/assets/distance_10_elevation_30_adv_pred.gif?raw=true'/></center></td>
+    <td><center><img src = 'https://github.com/winterwindwang/Full-coverage-camouflage-adversarial-attack/blob/gh-pages/assets/distance_10_elevation_40_adv_pred.gif?raw=true'/></center></td>
     <td><center><img src = 'https://github.com/winterwindwang/Full-coverage-camouflage-adversarial-attack/blob/gh-pages/assets/distance_10_elevation_50_adv_pred.gif?raw=true'/></center></td>
   </tr>
 </table>
 
-### Cases of Multi-view Attack
-
-
+### Partial occlusion 
 
 <table>
   <tr>
-  <td>before</td>
+  <td>Original</td>
   <td><center> <img src = 'https://github.com/winterwindwang/Full-coverage-camouflage-adversarial-attack/blob/gh-pages/assets/camera_distance_1.5_elevation_0_6_ori.png?raw=true'  width="100"/></center></td>
     <td><center><img src = 'https://github.com/winterwindwang/Full-coverage-camouflage-adversarial-attack/blob/gh-pages/assets/camera_distance_1.5_elevation_0_42_ori.png?raw=true' width="100" /> </center></td>
       <td><center><img src = 'https://github.com/winterwindwang/Full-coverage-camouflage-adversarial-attack/blob/gh-pages/assets/camera_distance_1.5_elevation_0_54_ori.png?raw=true' width="100" /> </center></td>
@@ -71,7 +98,7 @@ Source code can be find in [here](https://github.com/idrl-lab/Full-coverage-camo
     <td><center><img src = 'https://github.com/winterwindwang/Full-coverage-camouflage-adversarial-attack/blob/gh-pages/assets/camera_distance_1.5_elevation_20_78_ori.png?raw=true' width="100" /></center></td>
   </tr>
   <tr>
-    <td>after</td>
+    <td>FCA</td>
     <td><center> <img src = 'https://github.com/winterwindwang/Full-coverage-camouflage-adversarial-attack/blob/gh-pages/assets/camera_distance_1.5_elevation_0_6_adv.png?raw=true' width="100" /></center></td>
     <td><center><img src = 'https://github.com/winterwindwang/Full-coverage-camouflage-adversarial-attack/blob/gh-pages/assets/camera_distance_1.5_elevation_0_42_adv.png?raw=true' width="100" /> </center></td>
       <td><center><img src = 'https://github.com/winterwindwang/Full-coverage-camouflage-adversarial-attack/blob/gh-pages/assets/camera_distance_1.5_elevation_0_54_adv.png?raw=true' width="100" /> </center></td>
@@ -81,11 +108,9 @@ Source code can be find in [here](https://github.com/idrl-lab/Full-coverage-camo
   </tr>
 </table>
 
-The first row is the original detection result. The second row is the camouflaged detection result.
-
 <table>
   <tr>
-   <td>before</td>
+   <td>Original</td>
   <td><center> <img src = 'https://github.com/winterwindwang/Full-coverage-camouflage-adversarial-attack/blob/gh-pages/assets/camera_distance_5_elevation_10_57_ori.png?raw=true' width="100" /></center></td>
     <td><center><img src = 'https://github.com/winterwindwang/Full-coverage-camouflage-adversarial-attack/blob/gh-pages/assets/camera_distance_5_elevation_30_66_ori.png?raw=true' width="100" /> </center></td>
       <td><center><img src = 'https://github.com/winterwindwang/Full-coverage-camouflage-adversarial-attack/blob/gh-pages/assets/camera_distance_10_elevation_0_135_ori.png?raw=true' width="100" /> </center></td>
@@ -94,7 +119,7 @@ The first row is the original detection result. The second row is the camouflage
     <td><center><img src = 'https://github.com/winterwindwang/Full-coverage-camouflage-adversarial-attack/blob/gh-pages/assets/camera_distance_15_elevation_50_327_ori.png?raw=true' width="100" /></center></td>
   </tr>
   <tr>
-    <td>after</td>
+    <td>FCA</td>
   <td><center> <img src = 'https://github.com/winterwindwang/Full-coverage-camouflage-adversarial-attack/blob/gh-pages/assets/camera_distance_5_elevation_10_57_adv.png?raw=true' width="100" /></center></td>
     <td><center><img src = 'https://github.com/winterwindwang/Full-coverage-camouflage-adversarial-attack/blob/gh-pages/assets/camera_distance_5_elevation_30_66_adv.png?raw=true' width="100" /> </center></td>
       <td><center><img src = 'https://github.com/winterwindwang/Full-coverage-camouflage-adversarial-attack/blob/gh-pages/assets/camera_distance_10_elevation_0_135_adv.png?raw=true' width="100"/> </center></td>
@@ -104,7 +129,6 @@ The first row is the original detection result. The second row is the camouflage
   </tr>
 </table>
 
-The first row is the original detection result. The second row is the camouflaged detection result.
 
 ### Ablation study
 
@@ -130,3 +154,6 @@ As we can see from the Figure, different loss terms plays different roles in att
   <td><img src = 'https://github.com/winterwindwang/Full-coverage-camouflage-adversarial-attack/blob/gh-pages/assets/data13311_adv_zero.png?raw=true' width="200"/></td>
     </tr>
 </table>
+
+## Cases of Phyical Attack
+<iframe src="//player.bilibili.com/player.html?aid=379742176&bvid=BV1aZ4y197H8&cid=457802709&page=1" scrolling="no" border="0" frameborder="no" framespacing="0" allowfullscreen="true"> </iframe>