233 citations · 1.1k across the 34 of their papers we have counts for
9 papers · 1 filter
FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning
Hong-You Chen, Wei-Lun Chao
Federated learning aims to collaboratively train a strong global model by accessing users' locally trained models but not their own data. A crucial step is therefore to aggregate l…
Wasserstein Distances for Stereo Disparity Estimation
Divyansh Garg, Yan Wang, Bharath Hariharan +3
Existing approaches to depth or disparity estimation output a distribution over a set of pre-defined discrete values. This leads to inaccurate results when the true depth or dispar…
Train in Germany, Test in The USA: Making 3D Object Detectors Generalize
Yan Wang, Xiangyu Chen, Yurong You +5
In the domain of autonomous driving, deep learning has substantially improved the 3D object detection accuracy for LiDAR and stereo camera data alike. While deep networks are great…
End-to-End Pseudo-LiDAR for Image-Based 3D Object Detection
Rui Qian, Divyansh Garg, Yan Wang +6
Reliable and accurate 3D object detection is a necessity for safe autonomous driving. Although LiDAR sensors can provide accurate 3D point cloud estimates of the environment, they…
Interactive Natural Language-based Person Search
Vikram Shree, Wei-Lun Chao, Mark Campbell
In this work, we consider the problem of searching people in an unconstrained environment, with natural language descriptions. Specifically, we study how to systematically design a…
Revisiting Meta-Learning as Supervised Learning
Wei-Lun Chao, Han-Jia Ye, De-Chuan Zhan +2
Recent years have witnessed an abundance of new publications and approaches on meta-learning. This community-wide enthusiasm has sparked great insights but has also created a pleth…
An Empirical Study of Person Re-Identification with Attributes
Vikram Shree, Wei-Lun Chao, Mark Campbell
Person re-identification aims to identify a person from an image collection, given one image of that person as the query. There is, however, a plethora of real-life scenarios where…
Visual Question Answering on 360° Images
Shih-Han Chou, Wei-Lun Chao, Wei-Sheng Lai +2
In this work, we introduce VQA 360, a novel task of visual question answering on 360 images. Unlike a normal field-of-view image, a 360 image captures the entire visual content aro…
Identifying and Compensating for Feature Deviation in Imbalanced Deep Learning
Han-Jia Ye, Hong-You Chen, De-Chuan Zhan +1
Classifiers trained with class-imbalanced data are known to perform poorly on test data of the "minor" classes, of which we have insufficient training data. In this paper, we inves…