Search Results for author:
Found 11 papers, 6 papers with code
Test-Time Domain Adaptation by Learning Domain-Aware Batch Normalization
In this work, we propose to reduce such learning interference and elevate the domain knowledge learning by only manipulating the BN layer.
MetaGCD: Learning to Continually Learn in Generalized Category Discovery
The goal is to continually discover novel classes while maintaining the performance in known classes.
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.
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.
Self-supervised Spatiotemporal Representation Learning by Exploiting Video Continuity
Recent self-supervised video representation learning methods have found significant success by exploring essential properties of videos, e. g. speed, temporal order, etc.
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.
All at Once: Temporally Adaptive Multi-Frame Interpolation with Advanced Motion Modeling
Recent advances in high refresh rate displays as well as the increased interest in high rate of slow motion and frame up-conversion fuel the demand for efficient and cost-effective multi-frame video interpolation solutions.
Single Image Reflection Removal Using Deep Encoder-Decoder Network
Image of a scene captured through a piece of transparent and reflective material, such as glass, is often spoiled by a superimposed layer of reflection image.
