228 citations · 1.5k across the 123 of their papers we have counts for
8 papers · 1 filter
Posterior Re-calibration for Imbalanced Datasets
Junjiao Tian, Yen-Cheng Liu, Nathan Glaser +2
Neural Networks can perform poorly when the training label distribution is heavily imbalanced, as well as when the testing data differs from the training distribution. In order to…
3D for Free: Crossmodal Transfer Learning using HD Maps
Benjamin Wilson, Zsolt Kira, James Hays
3D object detection is a core perceptual challenge for robotics and autonomous driving. However, the class-taxonomies in modern autonomous driving datasets are significantly smalle…
FeatMatch: Feature-Based Augmentation for Semi-Supervised Learning
Chia-Wen Kuo, Chih-Yao Ma, Jia-Bin Huang +1
Recent state-of-the-art semi-supervised learning (SSL) methods use a combination of image-based transformations and consistency regularization as core components. Such methods, how…
Frustratingly Simple Domain Generalization via Image Stylization
Nathan Somavarapu, Chih-Yao Ma, Zsolt Kira
Convolutional Neural Networks (CNNs) show impressive performance in the standard classification setting where training and testing data are drawn i.i.d. from a given domain. Howeve…
When2com: Multi-Agent Perception via Communication Graph Grouping
Yen-Cheng Liu, Junjiao Tian, Nathaniel Glaser +1
While significant advances have been made for single-agent perception, many applications require multiple sensing agents and cross-agent communication due to benefits such as cover…
Generalized ODIN: Detecting Out-of-distribution Image without Learning from Out-of-distribution Data
Yen-Chang Hsu, Yilin Shen, Hongxia Jin +1
Deep neural networks have attained remarkable performance when applied to data that comes from the same distribution as that of the training set, but can significantly degrade othe…
Who2com: Collaborative Perception via Learnable Handshake Communication
Yen-Cheng Liu, Junjiao Tian, Chih-Yao Ma +3
In this paper, we propose the problem of collaborative perception, where robots can combine their local observations with those of neighboring agents in a learnable way to improve…
Action Segmentation with Joint Self-Supervised Temporal Domain Adaptation
Min-Hung Chen, Baopu Li, Yingze Bao +2
Despite the recent progress of fully-supervised action segmentation techniques, the performance is still not fully satisfactory. One main challenge is the problem of spatiotemporal…