AAAI Papers

Far3D: Expanding the Horizon for Surround

View 3D Object Detection

FashionERN: Enhance-and-Refine Network for Composed Fashion Image Retrieval

Yanzhe Chen, Huasong Zhong, Xiangteng He et al.

Fast and Controllable Post-training Sparsity: Learning Optimal Sparsity Allocation with Global Constraint in Minutes

Ruihao Gong, Yang Yong, Zining Wang et al.

Faster Stochastic Variance Reduction Methods for Compositional MiniMax Optimization

Jin Liu, Xiaokang Pan, Junwen Duan et al.

Fast Inter-frame Motion Prediction for Compressed Dynamic Point Cloud Attribute Enhancement

Wang Liu, Wei Gao, Xingming Mu

Fast Machine Unlearning without Retraining through Selective Synaptic Dampening

Jack Foster, Stefan Schoepf, Alexandra Brintrup

FAVOR: Full-Body AR-Driven Virtual Object Rearrangement Guided by Instruction Text

Kailin Li, Lixin Yang, Zenan Lin et al.

FD3D: Exploiting Foreground Depth Map for Feature-Supervised Monocular 3D Object Detection

Zizhang Wu, Yuanzhu Gan, Yunzhe Wu et al.

Feature Distribution Matching by Optimal Transport for Effective and Robust Coreset Selection

Feature Fusion from Head to Tail for Long-Tailed Visual Recognition

Mengke Li, Zhikai HU, Yang Lu et al.

Feature Transportation Improves Graph Neural Networks

Moshe Eliasof, Eldad Haber, Eran Treister

FeatWalk: Enhancing Few-Shot Classification through Local View Leveraging

Dalong Chen, Jianjia Zhang, Wei-shi Zheng et al.

FedA3I: Annotation Quality-Aware Aggregation for Federated Medical Image Segmentation against Heterogeneous Annotation Noise

Nannan Wu, Zhaobin Sun, Zengqiang Yan et al.

FedASMU: Efficient Asynchronous Federated Learning with Dynamic Staleness-Aware Model Update

Ji Liu, Juncheng Jia, Tianshi Che et al.

FedCD: Federated Semi-supervised Learning with Class Awareness Balance via Dual Teachers

Yuzhi Liu, Huisi Wu, Jing Qin

FedCompetitors: Harmonious Collaboration in Federated Learning with Competing Participants

Shanli Tan, Hao Cheng, Xiaohu Wu et al.

FedCSL: A Scalable and Accurate Approach to Federated Causal Structure Learning

Xianjie Guo, Kui Yu, Lin Liu et al.

FedDAT: An Approach for Foundation Model Finetuning in Multi-Modal Heterogeneous Federated Learning

Haokun Chen, Yao Zhang, Denis Krompass et al.

FedDiv: Collaborative Noise Filtering for Federated Learning with Noisy Labels

Authors: Jichang Li, Guanbin Li, Hui Cheng et al.

Federated Adaptive Prompt Tuning for Multi-Domain Collaborative Learning

Shangchao Su, Mingzhao Yang, Bin Li et al.

Federated Causality Learning with Explainable Adaptive Optimization

Dezhi Yang, Xintong He, Jun Wang et al.

Federated Contextual Cascading Bandits with Asynchronous Communication and Heterogeneous Users

Hantao Yang, Xutong Liu, Zhiyong Wang et al.

Federated Graph Learning under Domain Shift with Generalizable Prototypes

Guancheng Wan, Wenke Huang, Mang Ye

Federated Label-Noise Learning with Local Diversity Product Regularization

Xiaochen Zhou, Xudong Wang

Federated Learning with Extremely Noisy Clients via Negative Distillation

Yang Lu, Lin Chen, Yonggang Zhang et al.

Federated Modality-Specific Encoders and Multimodal Anchors for Personalized Brain Tumor Segmentation

Federated Partial Label Learning with Local-Adaptive Augmentation and Regularization

Yan Yan, Yuhong Guo

FedFixer: Mitigating Heterogeneous Label Noise in Federated Learning

Xinyuan Ji, Zhaowei Zhu, Wei Xi et al.

FedGCR: Achieving Performance and Fairness for Federated Learning with Distinct Client Types via Group Customization and Reweighting

Shu-Ling Cheng, Chin-Yuan Yeh, Ting-An Chen et al.

FedLF: Layer-Wise Fair Federated Learning

Zibin Pan, Chi Li, Fangchen Yu et al.

FedLPS: Heterogeneous Federated Learning for Multiple Tasks with Local Parameter Sharing

Yongzhe Jia, Xuyun Zhang, Amin Beheshti et al.

FedMut: Generalized Federated Learning via Stochastic Mutation

Ming Hu, Cao Yue, Anran Li et al.

FedNS: A Fast Sketching Newton-Type Algorithm for Federated Learning

Jian Li, Yong Liu, Wei Wang et al.

Fed-QSSL: A Framework for Personalized Federated Learning under Bitwidth and Data Heterogeneity

Yiyue Chen, Haris Vikalo, Chianing Wang

FedST: Federated Style Transfer Learning for Non-IID Image Segmentation

Boyuan Ma, Yin Xiang, Jing Tan et al.

FedTGP: Trainable Global Prototypes with Adaptive-Margin-Enhanced Contrastive Learning for

Jianqing Zhang, Yang Liu, Yang Hua et al.

Fewer Steps, Better Performance: Efficient Cross-Modal Clip Trimming for Video Moment Retrieval Using Language

Xiang Fang, Daizong Liu, Wanlong Fang et al.

Few-Shot Learning from Augmented Label-Uncertain Queries in Bongard-HOI

Qinqian Lei, Bo Wang, Robby T. Tan

Few-Shot Neural Radiance Fields under Unconstrained Illumination

SeokYeong Lee, JunYong Choi, Seungryong Kim et al.

Few Shot Part Segmentation Reveals Compositional Logic for Industrial Anomaly Detection

Soopil Kim, Sion An, Philip Chikontwe et al.

FFT-Based Dynamic Token Mixer for Vision

Yuki Tatsunami, Masato Taki

FG-EmoTalk: Talking Head Video Generation with Fine-Grained Controllable Facial Expressions

Zhaoxu Sun, Yuze Xuan, Fang Liu et al.

Finding Interpretable Class-Specific Patterns through Efficient Neural Search

Nils Philipp Walter, Jonas Fischer, Jilles Vreeken

Finding Visual Saliency in Continuous Spike Stream

Lin Zhu, Xianzhang Chen, Xiao Wang et al.

Fine-Grained Distillation for Long Document Retrieval

Yucheng Zhou, Tao Shen, Xiubo Geng et al.

Fine-Grained Knowledge Selection and Restoration for Non-exemplar Class Incremental Learning

Authors: Jiang-Tian Zhai, Xialei Liu, Lu Yu et al.

Fine-Grained Multi-View Hand Reconstruction Using Inverse Rendering

Qijun Gan, Wentong Li, Jinwei Ren et al.

Fine-Grained Prototypes Distillation for Few-Shot Object Detection

Zichen Wang, Bo Yang, Haonan Yue et al.

Fine Structure-Aware Sampling: A New Sampling Training Scheme for Pixel-Aligned Implicit Models in Single-View Human Reconstruction

K. Chan, Fayao Liu, Guosheng Lin et al.

Fine-Tuning Graph Neural Networks by Preserving Graph Generative Patterns

Yifei Sun, Qi Zhu, Yang Yang et al.