6 citations · 8 across the 4 of their papers we have counts for
6 papers
Image-to-Image Translation for Autonomous Driving from Coarsely-Aligned Image Pairs
Youya Xia, Josephine Monica, Wei-Lun Chao +3
A self-driving car must be able to reliably handle adverse weather conditions (e.g., snowy) to operate safely. In this paper, we investigate the idea of turning sensor inputs (i.e.…
Learning to Detect Mobile Objects from LiDAR Scans Without Labels
Yurong You, Katie Z Luo, Cheng Perng Phoo +5
Current 3D object detectors for autonomous driving are almost entirely trained on human-annotated data. Although of high quality, the generation of such data is laborious and costl…
Revisiting Document Representations for Large-Scale Zero-Shot Learning
Jihyung Kil, Wei-Lun Chao
Zero-shot learning aims to recognize unseen objects using their semantic representations. Most existing works use visual attributes labeled by humans, not suitable for large-scale…
Procrustean Training for Imbalanced Deep Learning
Han-Jia Ye, De-Chuan Zhan, Wei-Lun Chao
Neural networks trained with class-imbalanced data are known to perform poorly on minor classes of scarce training data. Several recent works attribute this to over-fitting to mino…
MosaicOS: A Simple and Effective Use of Object-Centric Images for Long-Tailed Object Detection
Cheng Zhang, Tai-Yu Pan, Yandong Li +5
Many objects do not appear frequently enough in complex scenes (e.g., certain handbags in living rooms) for training an accurate object detector, but are often found frequently by…
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…