update

fullpubs.html

@@ -277,7 +277,7 @@ <h2 id="confpapers"><a name="Co-Author">Co-Author Papers</a></h2>
 <p>
   <br>[<a id="J8" name="J8"></a>J.8]
   <strong>SoftPatch+: Fully unsupervised anomaly classification and segmentation</strong> [<a href=https://doi.org/10.1016/j.patcog.2024.111295>pdf</a>]
-  <br> C. Wang, X. Jiang, <strong>B.-B. Gao</strong>, Z. Gan, Y. Liu, F. Zheng, L. Ma#
+  <br> C. Wang, X. Jiang<sup>i</sup>, <strong>B.-B. Gao</strong>, Z. Gan, Y. Liu, F. Zheng, L. Ma#
   <br> Pattern Recognition (<strong>PR</strong>), 2024. [<span style="color:red;"><strong>CCF-B, SCI-1, IF:8.0</strong></span>]
 </p> 
 

index.html

@@ -130,7 +130,7 @@ <h2> <a name="Biography">Biography</a>
   <h2><a name="Research">Research</a></h2>
   <div class="paper">
   <ul>
-  My current focus is on studying <font color="red">simple and general</font> (more essential and practical) methods/models for computer vision applications under various constraints, including zero/few-shot, long-tail, continual, unsupervised, etc.
+  My current focus is developing <font color="red">simple and general</font> (more essential and practical) methods/models for computer vision applications (especially on industrial or medical anomaly detection), under various constraints, such as zero-shot, few-shot, long-tail, continual, unsupervised and open-world.
   </ul>
   <br>
   <ul>
@@ -139,30 +139,30 @@ <h2><a name="Research">Research</a></h2>
   <ul>
   <li>Image Classification [<a href="https://arxiv.org/pdf/2304.10093.pdf">IJCAI 23</a>], Semantic Segmentation [<a href="https://ieeexplore.ieee.org/document/9773019">TMM 22</a>]</li>
   <li>Object Detection and Instance Segmentation [<a href="https://proceedings.neurips.cc/paper_files/paper/2022/file/764ba7236fb63743014fafbd87dd4f0e-Paper-Conference.pdf">NeurIPS 22</a>],
-      Object Counting  
+      Object Counting [<a href="https://www.sciencedirect.com/journal/pattern-recognition">PR</a>] </li>
+  <li>Few-shot Anomaly Generation 🚀🚀 <a href="./Pub_files/ECCV2024_AnoGen_CR_0730_Mobile.pdf">[ECCV 2024]</a> 
+
   </li>
 
   </ul>
   <li><strong>Continual Learning</a></strong></li>
   <ul>
   <li>Image Classification [<a href="https://ieeexplore.ieee.org/abstract/document/10347466">TMM 23</a>],
-      Object Detection [<a href="https://cs.nju.edu.cn/_upload/tpl/00/ed/237/template237/paper/AAAI2016_D3.pdf">AAAI 24</a>]</li>
+      Object Detection [<a href="https://doi.org/10.1609/aaai.v38i7.28537">AAAI 24</a>],
+      Anomaly Detection [<a href="https://ojs.aaai.org/index.php/AAAI/article/view/28153">AAAI 24</a>]</li>
   </ul>
   <li><strong>Unsupervised Anomaly Detection</strong></li>
   <ul>
-  <li>Unified AD
-    <a href="https://eccv.ecva.net/">[ECCV 2024]</a>,
-      Universal AD,
-      Fully Unsupervised AD [<a href="">CVPR 24</a>],
-      Few-shot Anomaly Generation 
-    <a href="https://eccv.ecva.net/">[ECCV 2024]</a>
+  <li>Unified AD 🚀🚀 <a href="./Pub_files/ECCV2024_OneNIP_CR_Full_0725_Mobile.pdf">[ECCV 2024]</a>,
+      Universal AD [<a href="https://nips.cc/Conferences/2024/">NeurIPS 24</a>],
+      Fully Unsupervised AD [<a href="https://openaccess.thecvf.com/content/CVPR2024/papers/Wang_Real-IAD_A_Real-World_Multi-View_Dataset_for_Benchmarking_Versatile_Industrial_Anomaly_CVPR_2024_paper.pdf">CVPR 24</a>]
   </li>
   </ul>
   <li><strong>General Object Recognition</strong></li>
   <ul>
   <li>Multi-Label Image Recognition [<a href="https://ieeexplore.ieee.org/document/9466402">TIP 21</a>],
-      Change Detection [<a href="https://arxiv.org/pdf/2206.07557.pdf">PR 22</a>], 
-      Open-Vocabulary Object Detection</li>
+      Change Detection [<a href="https://doi.org/10.1016/j.patcog.2023.109384">PR 22</a>], 
+      Open-World Object Detection with Visual Prompts</li>
   </ul>
   <li><strong>Earlier Works</strong></li>
   <ul>
@@ -246,6 +246,8 @@ <h2><a name="Selected Publications">Selected Publications</a></h2>
 [<a href="http://scholar.google.com/citations?user=yYviZ-oAAAAJ&hl=en">Google Scholar</a>]
 </p>
 
+* equal contribution, <sup>i</sup> my intern, <sup>#</sup> corresponding author
+
 <ul>
 <li>
 <p>