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Found 8 papers, 5 papers with code
Test-Time Personalization with Meta Prompt for Gaze Estimation
Despite the recent remarkable achievement in gaze estimation, efficient and accurate personalization of gaze estimation without labels is a practical problem but rarely touched on in the literature.
Meta-DMoE: Adapting to Domain Shift by Meta-Distillation from Mixture-of-Experts
Most existing methods perform training on multiple source domains using a single model, and the same trained model is used on all unseen target domains.
Ranked #22 on
Domain Generalization
on DomainNet
Improving ProtoNet for Few-Shot Video Object Recognition: Winner of ORBIT Challenge 2022
In this work, we present the winning solution for ORBIT Few-Shot Video Object Recognition Challenge 2022.
Error-Aware Spatial Ensembles for Video Frame Interpolation
However, none of the published VFI works considers the spatially non-uniform characteristics of the interpolation error (IE).
Few-Shot Class-Incremental Learning via Entropy-Regularized Data-Free Replay
In this paper, we show through empirical results that adopting the data replay is surprisingly favorable.
S-Rocket: Selective Random Convolution Kernels for Time Series Classification
A population-based optimization algorithm evolves the population in order to find a best state vector which minimizes the number of active kernels while maximizing the accuracy of the classifier.
MetaFSCIL: A Meta-Learning Approach for Few-Shot Class Incremental Learning
The learning objective of these methods is often hand-engineered and is not directly tied to the objective (i. e. incrementally learning new classes) during testing.
Test-Time Fast Adaptation for Dynamic Scene Deblurring via Meta-Auxiliary Learning
Therefore, we are able to exploit the internal information at test time via the auxiliary task to enhance the performance of deblurring.
