In the problem of out-of-distribution (OOD) detection, the usage of auxi...
In the field of out-of-distribution (OOD) detection, a previous method t...
This paper investigates a missing feature imputation problem for graph
l...
Recently, large-scale vision-language pre-training models and visual sem...
Automatic audio event recognition plays a pivotal role in making human r...
Fonts can convey profound meanings of words in various forms of glyphs.
...
Existing message passing neural networks for heterogeneous graphs rely o...
We propose a new transformer model for the task of unsupervised learning...
The key to successful grounding for video surveillance is to understand ...
A well-designed strong-weak augmentation strategy and the stable teacher...
The problem of class imbalanced data lies in that the generalization
per...
In this paper, we propose a balancing training method to address problem...
Due to the increasing need to handle the noisy label problem in a massiv...
Most of the existing literature regarding hyperbolic embedding concentra...
One of the most rising issues in recent machine learning research is
One...
We propose Aggregation with Class-Attentive Diffusion (AggCAD), a novel
...
Existing fine-tuning methods use a single learning rate over all layers....
Recently, several studies proposed methods to utilize some restricted cl...
This paper proposes a new high dimensional regression method by merging
...
We propose a symmetric graph convolutional autoencoder which produces a
...
In this paper, we propose a novel structure for a cross-modal data
assoc...
Mathematical optimization is widely used in various research fields. Wit...
We investigate the design aspects of feature distillation methods achiev...
In visual surveillance systems, it is necessary to recognize the behavio...
In person re-identification (ReID) task, because of its shortage of trai...
An activation boundary for a neuron refers to a separating hyperplane th...
Many recent works on knowledge distillation have provided ways to transf...
Many recent works on knowledge distillation have provided ways to transf...
We propose a new context-aware correlation filter based tracking framewo...