Papers
F-Bench: Rethinking Human Preference Evaluation Metrics for Benchmarking Face Generation, Customization, and Restoration
Lu Liu, Huiyu Duan, Qiang Hu et al.
FDPT: Federated Discrete Prompt Tuning for Black-Box Visual-Language Models
Jiaqi Wu, Simin Chen, Jing Tang et al.
Feather the Throttle: Revisiting Visual Token Pruning for Vision-Language Model Acceleration
Mark Endo, Xiaohan Wang, Serena Yeung-Levy
Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark
Changsheng Gao, Yifan Ma, Qiaoxi Chen et al.
Feature Decomposition-Recomposition in Large Vision-Language Model for Few-Shot Class-Incremental Learning
Zongyao Xue, Meina Kan, Shiguang Shan et al.
Feature Extraction and Representation of Pre-training Point Cloud Based on Diffusion Models
Chang Qiu, Feipeng Da, Zilei Zhang
Feature Purification Matters: Suppressing Outlier Propagation for Training-Free Open-Vocabulary Semantic Segmentation
Shuo Jin, Siyue Yu, Bingfeng Zhang et al.
2025
ICCV
FE-CLIP: Frequency Enhanced CLIP Model for Zero-Shot Anomaly Detection and Segmentation
Tao Gong, Qi Chu, Bin Liu et al.
FedAGC: Federated Continual Learning with Asymmetric Gradient Correction
Chengchao Zhang, Fanhua Shang, Hongying Liu et al.
FedDifRC: Unlocking the Potential of Text-to-Image Diffusion Models in Heterogeneous Federated Learning
Huan Wang, Haoran Li, Huaming Chen et al.
Federated Continual Instruction Tuning
Haiyang Guo, Fanhu Zeng, Fei Zhu et al.
Federated Continuous Category Discovery and Learning
Lixu Wang, Chenxi Liu, Junfeng Guo et al.
Federated Domain Generalization with Domain-specific Soft Prompts Generation
Jianhan Wu, Xiaoyang Qu, Zhangcheng Huang et al.
Federated Prompt-Tuning with Heterogeneous and Incomplete Multimodal Client Data
Thu Hang Phung, Duong M. Nguyen, Thanh Trung Huynh et al.
Federated Representation Angle Learning
Liping Yi, Han Yu, Gang Wang et al.
FedMeNF: Privacy-Preserving Federated Meta-Learning for Neural Fields
Junhyeog Yun, Minui Hong, Gunhee Kim
FedMVP: Federated Multimodal Visual Prompt Tuning for Vision-Language Models
Mainak Singha, Subhankar Roy, Sarthak Mehrotra et al.
FedPall: Prototype-based Adversarial and Collaborative Learning for Federated Learning with Feature Drift
Yong Zhang, Feng Liang, Guanghu Yuan et al.
FED-PsyAU: Privacy-Preserving Micro-Expression Recognition via Psychological AU Coordination and Dynamic Facial Motion Modeling
Jingting Li, Yu Qian, Lin Zhao et al.
FedVLA: Federated Vision-Language-Action Learning with Dual Gating Mixture-of-Experts for Robotic Manipulation
Cui Miao, Tao Chang, Meihan Wu et al.
FedWSQ: Efficient Federated Learning with Weight Standardization and Distribution-Aware Non-Uniform Quantization
Seung-Wook Kim, Seongyeol Kim, Jiah Kim et al.
FedXDS: Leveraging Model Attribution Methods to counteract Data Heterogeneity in Federated Learning
Maximilian Andreas Hoefler, Karsten Mueller, Wojciech Samek
Feed-Forward SceneDINO for Unsupervised Semantic Scene Completion
Aleksandar Jevtić, Christoph Reich, Felix Wimbauer et al.
FEVER-OOD: Free Energy Vulnerability Elimination for Robust Out-of-Distribution Detection
Brian K.S. Isaac-Medina, Mauricio Che, Yona Falinie A. Gaus et al.
Fewer Denoising Steps or Cheaper Per-Step Inference: Towards Compute-Optimal Diffusion Model Deployment
Zhenbang Du, Yonggan Fu, Lifu Wang et al.