🏢 South China University of Technology

UMB: A novel model enhances open-world object detection by understanding model behavior, surpassing state-of-the-art with a 5.3 mAP gain for unknown classes.

TAPTRv2 enhances point tracking by introducing an attention-based position update, eliminating cost-volume reliance for improved accuracy and efficiency.

SelfFormer: A novel self-supervised transformer-based method outperforms existing techniques by leveraging directional self-attention for efficient and accurate real-world image denoising.

KEDGN, a novel graph neural network, leverages medical knowledge to model variable-specific temporal dependencies and dynamic inter-variable correlations in irregularly sampled medical time series, si…

Meta-learning enhances human mesh recovery by unifying training and test-time objectives, significantly improving accuracy and generalization.

GACL: a novel exemplar-free technique for generalized analytic continual learning, achieves superior performance by analytically solving the weight-invariant property for handling real-world data.

F-OAL: Forward-only Online Analytic Learning achieves high accuracy and low memory usage in online class incremental learning by using a frozen encoder and recursive least squares to update a linear …

CycleNet enhances long-term time series forecasting by explicitly modeling inherent periodic patterns using a novel Residual Cycle Forecasting technique, achieving state-of-the-art accuracy and effici…

CoLA: Collaborative Lifelong Adaptation boosts test-time adaptation efficiency by sharing domain knowledge across multiple devices, achieving significant accuracy gains with minimal computational over…