15 citations · 57 across the 21 of their papers we have counts for
5 papers · 1 filter
Exploring Covariate and Concept Shift for Detection and Calibration of Out-of-Distribution Data
Junjiao Tian, Yen-Change Hsu, Yilin Shen +2
Moving beyond testing on in-distribution data works on Out-of-Distribution (OOD) detection have recently increased in popularity. A recent attempt to categorize OOD data introduces…
A Geometric Perspective towards Neural Calibration via Sensitivity Decomposition
Junjiao Tian, Dylan Yung, Yen-Chang Hsu +1
It is well known that vision classification models suffer from poor calibration in the face of data distribution shifts. In this paper, we take a geometric approach to this problem…
Overcoming Obstructions via Bandwidth-Limited Multi-Agent Spatial Handshaking
Nathaniel Glaser, Yen-Cheng Liu, Junjiao Tian +1
In this paper, we address bandwidth-limited and obstruction-prone collaborative perception, specifically in the context of multi-agent semantic segmentation. This setting presents…
Enhancing Multi-Robot Perception via Learned Data Association
Nathaniel Glaser, Yen-Cheng Liu, Junjiao Tian +1
In this paper, we address the multi-robot collaborative perception problem, specifically in the context of multi-view infilling for distributed semantic segmentation. This setting…
Striking the Right Balance: Recall Loss for Semantic Segmentation
Junjiao Tian, Niluthpol Mithun, Zach Seymour +2
Class imbalance is a fundamental problem in computer vision applications such as semantic segmentation. Specifically, uneven class distributions in a training dataset often result…