auto update @ 2024-09-30T10:58:28Z Asia/Shanghai

youngfish42 · Sep 30, 2024 · f30648e · f30648e
1 parent 22ca71d
commit f30648e
Show file tree

Hide file tree

Showing 2 changed files with 35 additions and 4 deletions.
diff --git a/README.md b/README.md
@@ -1219,10 +1219,10 @@ Federated Learning papers accepted by top CV(computer vision) conference and jou
 | An Upload-Efficient Scheme for Transferring Knowledge From a Server-Side Pre-trained Generator to Clients in Heterogeneous Federated Learning | SJTU | CVPR | 2024 | [[PUB](https://openaccess.thecvf.com/content/CVPR2024/html/Zhang_An_Upload-Efficient_Scheme_for_Transferring_Knowledge_From_a_Server-Side_Pre-trained_CVPR_2024_paper.html)] [[SUPP](https://openaccess.thecvf.com/content/CVPR2024/supplemental/Zhang_An_Upload-Efficient_Scheme_CVPR_2024_supplemental.zip)] [[PDF](https://arxiv.org/abs/2403.15760)] [[CODE](https://github.com/tsingz0/fedktl)] [[POSTER](https://github.com/TsingZ0/FedKTL/blob/main/FedKTL.png)] [[SLIDES](https://github.com/TsingZ0/FedKTL/blob/main/FedKTL.pdf)] |
 | An Aggregation-Free Federated Learning for Tackling Data Heterogeneity | A* STAR | CVPR | 2024 | [[PUB](https://openaccess.thecvf.com/content/CVPR2024/html/Wang_An_Aggregation-Free_Federated_Learning_for_Tackling_Data_Heterogeneity_CVPR_2024_paper.html)] [[SUPP](https://openaccess.thecvf.com/content/CVPR2024/supplemental/Wang_An_Aggregation-Free_Federated_CVPR_2024_supplemental.pdf)] [[PDF](https://arxiv.org/abs/2404.18962)] |
 | FLHetBench: Benchmarking Device and State Heterogeneity in Federated Learning | BUAA; HKU | CVPR | 2024 | [[PUB](https://openaccess.thecvf.com/content/CVPR2024/html/Zhang_FLHetBench_Benchmarking_Device_and_State_Heterogeneity_in_Federated_Learning_CVPR_2024_paper.html)] [[SUPP](https://openaccess.thecvf.com/content/CVPR2024/supplemental/Zhang_FLHetBench_Benchmarking_Device_CVPR_2024_supplemental.pdf)] [[CODE](https://github.com/Carkham/FLHetBench)] [[PAGE](https://carkham.github.io/FL_Het_Bench/)] [[POSTER](https://drive.google.com/file/d/1Ln0cnptSn5EfML6ughQ7NowwjjLfMYgu/view?usp=sharing)] [[VIDEO](https://www.youtube.com/watch?v=zDGPt3929l8)] |
-| Collaborative Visual Place Recognition through Federated Learning |  | CVPR workshop | 2024 | [PUB](https://openaccess.thecvf.com/content/CVPR2024W/FedVision-2024/html/Dutto_Collaborative_Visual_Place_Recognition_through_Federated_Learning_CVPRW_2024_paper.html) [SUPP](https://openaccess.thecvf.com/content/CVPR2024W/FedVision-2024/supplemental/Dutto_Collaborative_Visual_Place_CVPRW_2024_supplemental.pdf) [PDF](http://arxiv.org/abs/2404.13324) |
-| FedProK: Trustworthy Federated Class-Incremental Learning via Prototypical Feature Knowledge Transfer |  | CVPR workshop | 2024 | [PUB](https://openaccess.thecvf.com/content/CVPR2024W/FedVision-2024/html/Gao_FedProK_Trustworthy_Federated_Class-Incremental_Learning_via_Prototypical_Feature_Knowledge_Transfer_CVPRW_2024_paper.html) [SUPP](https://openaccess.thecvf.com/content/CVPR2024W/FedVision-2024/supplemental/Gao_FedProK_Trustworthy_Federated_CVPRW_2024_supplemental.pdf) [PDF](http://arxiv.org/abs/2405.02685) |
-| Federated Hyperparameter Optimization Through Reward-Based Strategies: Challenges and Insights |  | CVPR workshop | 2024 | [PUB](https://openaccess.thecvf.com/content/CVPR2024W/FedVision-2024/html/Nakka_Federated_Hyperparameter_Optimization_Through_Reward-Based_Strategies_Challenges_and_Insights_CVPRW_2024_paper.html) |
-| On the Efficiency of Privacy Attacks in Federated Learning |  | CVPR workshop | 2024 | [PUB](https://openaccess.thecvf.com/content/CVPR2024W/FedVision-2024/html/Tabassum_On_the_Efficiency_of_Privacy_Attacks_in_Federated_Learning_CVPRW_2024_paper.html) [PDF](http://arxiv.org/abs/2404.09430) |
+| Collaborative Visual Place Recognition through Federated Learning |  | CVPR workshop | 2024 | [[PUB](https://openaccess.thecvf.com/content/CVPR2024W/FedVision-2024/html/Dutto_Collaborative_Visual_Place_Recognition_through_Federated_Learning_CVPRW_2024_paper.html)] [[SUPP](https://openaccess.thecvf.com/content/CVPR2024W/FedVision-2024/supplemental/Dutto_Collaborative_Visual_Place_CVPRW_2024_supplemental.pdf)] [[PDF](http://arxiv.org/abs/2404.13324)] |
+| FedProK: Trustworthy Federated Class-Incremental Learning via Prototypical Feature Knowledge Transfer |  | CVPR workshop | 2024 | [[PUB](https://openaccess.thecvf.com/content/CVPR2024W/FedVision-2024/html/Gao_FedProK_Trustworthy_Federated_Class-Incremental_Learning_via_Prototypical_Feature_Knowledge_Transfer_CVPRW_2024_paper.html)] [[SUPP](https://openaccess.thecvf.com/content/CVPR2024W/FedVision-2024/supplemental/Gao_FedProK_Trustworthy_Federated_CVPRW_2024_supplemental.pdf)] [[PDF](http://arxiv.org/abs/2405.02685)] |
+| Federated Hyperparameter Optimization Through Reward-Based Strategies: Challenges and Insights |  | CVPR workshop | 2024 | [[PUB](https://openaccess.thecvf.com/content/CVPR2024W/FedVision-2024/html/Nakka_Federated_Hyperparameter_Optimization_Through_Reward-Based_Strategies_Challenges_and_Insights_CVPRW_2024_paper.html)] |
+| On the Efficiency of Privacy Attacks in Federated Learning |  | CVPR workshop | 2024 | [[PUB](https://openaccess.thecvf.com/content/CVPR2024W/FedVision-2024/html/Tabassum_On_the_Efficiency_of_Privacy_Attacks_in_Federated_Learning_CVPRW_2024_paper.html)] [[PDF](http://arxiv.org/abs/2404.09430)] |
 | FedCE: Personalized Federated Learning Method based on Clustering Ensembles | BJTU | MM | 2023 | [[PUB](https://dl.acm.org/doi/10.1145/3581783.3612217)] |
 | FedVQA: Personalized Federated Visual Question Answering over Heterogeneous Scenes | Leiden University | MM | 2023 | [[PUB](https://dl.acm.org/doi/10.1145/3581783.3611958)] |
 | Towards Fast and Stable Federated Learning: Confronting Heterogeneity via Knowledge Anchor | XJTU | MM | 2023 | [[PUB](https://dl.acm.org/doi/10.1145/3581783.3612597)] [[PDF](https://arxiv.org/abs/2312.02416)] [[CODE](https://github.com/J1nqianChen/FedKA)] |

diff --git a/data.yaml b/data.yaml
@@ -9341,6 +9341,37 @@ fl-in-top-cv-conference-and-journal:
       PAGE: https://carkham.github.io/FL_Het_Bench/
       POSTER: https://drive.google.com/file/d/1Ln0cnptSn5EfML6ughQ7NowwjjLfMYgu/view?usp=sharing
       VIDEO: https://www.youtube.com/watch?v=zDGPt3929l8
+  - title: Collaborative Visual Place Recognition through Federated Learning
+    affiliation: ''
+    venue: CVPR workshop
+    year: '2024'
+    materials:
+      PUB: https://openaccess.thecvf.com/content/CVPR2024W/FedVision-2024/html/Dutto_Collaborative_Visual_Place_Recognition_through_Federated_Learning_CVPRW_2024_paper.html
+      SUPP: https://openaccess.thecvf.com/content/CVPR2024W/FedVision-2024/supplemental/Dutto_Collaborative_Visual_Place_CVPRW_2024_supplemental.pdf
+      PDF: http://arxiv.org/abs/2404.13324
+  - title: 'FedProK: Trustworthy Federated Class-Incremental Learning via Prototypical
+      Feature Knowledge Transfer'
+    affiliation: ''
+    venue: CVPR workshop
+    year: '2024'
+    materials:
+      PUB: https://openaccess.thecvf.com/content/CVPR2024W/FedVision-2024/html/Gao_FedProK_Trustworthy_Federated_Class-Incremental_Learning_via_Prototypical_Feature_Knowledge_Transfer_CVPRW_2024_paper.html
+      SUPP: https://openaccess.thecvf.com/content/CVPR2024W/FedVision-2024/supplemental/Gao_FedProK_Trustworthy_Federated_CVPRW_2024_supplemental.pdf
+      PDF: http://arxiv.org/abs/2405.02685
+  - title: 'Federated Hyperparameter Optimization Through Reward-Based Strategies:
+      Challenges and Insights'
+    affiliation: ''
+    venue: CVPR workshop
+    year: '2024'
+    materials:
+      PUB: https://openaccess.thecvf.com/content/CVPR2024W/FedVision-2024/html/Nakka_Federated_Hyperparameter_Optimization_Through_Reward-Based_Strategies_Challenges_and_Insights_CVPRW_2024_paper.html
+  - title: On the Efficiency of Privacy Attacks in Federated Learning
+    affiliation: ''
+    venue: CVPR workshop
+    year: '2024'
+    materials:
+      PUB: https://openaccess.thecvf.com/content/CVPR2024W/FedVision-2024/html/Tabassum_On_the_Efficiency_of_Privacy_Attacks_in_Federated_Learning_CVPRW_2024_paper.html
+      PDF: http://arxiv.org/abs/2404.09430
   - title: 'FedCE: Personalized Federated Learning Method based on Clustering Ensembles'
     affiliation: BJTU
     venue: MM