22 citations · 31 across the 7 of their papers we have counts for
7 papers
A Two-Block RNN-based Trajectory Prediction from Incomplete Trajectory
Ryo Fujii, Jayakorn Vongkulbhisal, Ryo Hachiuma +1
Trajectory prediction has gained great attention and significant progress has been made in recent years. However, most works rely on a key assumption that each video is successfull…
On Focal Loss for Class-Posterior Probability Estimation: A Theoretical Perspective
Nontawat Charoenphakdee, Jayakorn Vongkulbhisal, Nuttapong Chairatanakul +1
The focal loss has demonstrated its effectiveness in many real-world applications such as object detection and image classification, but its theoretical understanding has been limi…
Learning Multiple Sound Source 2D Localization
Guillaume Le Moing, Phongtharin Vinayavekhin, Tadanobu Inoue +4
In this paper, we propose novel deep learning based algorithms for multiple sound source localization. Specifically, we aim to find the 2D Cartesian coordinates of multiple sound s…
Ensemble of Discriminators for Domain Adaptation in Multiple Sound Source 2D Localization
Guillaume Le Moing, Don Joven Agravante, Tadanobu Inoue +4
This paper introduces an ensemble of discriminators that improves the accuracy of a domain adaptation technique for the localization of multiple sound sources. Recently, deep neura…
Data-Efficient Framework for Real-world Multiple Sound Source 2D Localization
Guillaume Le Moing, Phongtharin Vinayavekhin, Don Joven Agravante +4
Deep neural networks have recently led to promising results for the task of multiple sound source localization. Yet, they require a lot of training data to cover a variety of acous…
Unifying Heterogeneous Classifiers with Distillation
Jayakorn Vongkulbhisal, Phongtharin Vinayavekhin, Marco Visentini-Scarzanella
In this paper, we study the problem of unifying knowledge from a set of classifiers with different architectures and target classes into a single classifier, given only a generic s…
Discriminative Optimization: Theory and Applications to Computer Vision Problems
Jayakorn Vongkulbhisal, Fernando De la Torre, João P. Costeira
Many computer vision problems are formulated as the optimization of a cost function. This approach faces two main challenges: (i) designing a cost function with a local optimum at…