most citedUnsupervised Adaptation from Repeated Traversals for Autonomous Driving

5 citations · 6 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024

Better Monocular 3D Detectors with LiDAR from the Past

Yurong You, Cheng Perng Phoo, Carlos Andres Diaz-Ruiz +5

Accurate 3D object detection is crucial to autonomous driving. Though LiDAR-based detectors have achieved impressive performance, the high cost of LiDAR sensors precludes their wid…

cs.CV20231 cited

Reward Finetuning for Faster and More Accurate Unsupervised Object Discovery

Katie Z Luo, Zhenzhen Liu, Xiangyu Chen +7

Recent advances in machine learning have shown that Reinforcement Learning from Human Feedback (RLHF) can improve machine learning models and align them with human preferences. Alt…

cs.CV2023

Unsupervised Domain Adaptation for Self-Driving from Past Traversal Features

Travis Zhang, Katie Luo, Cheng Perng Phoo +5

The rapid development of 3D object detection systems for self-driving cars has significantly improved accuracy. However, these systems struggle to generalize across diverse driving…

cs.CV2023

Distilling from Similar Tasks for Transfer Learning on a Budget

Kenneth Borup, Cheng Perng Phoo, Bharath Hariharan

We address the challenge of getting efficient yet accurate recognition systems with limited labels. While recognition models improve with model size and amount of data, many specia…

cs.CV20235 cited

Unsupervised Adaptation from Repeated Traversals for Autonomous Driving

Yurong You, Cheng Perng Phoo, Katie Z Luo +5

For a self-driving car to operate reliably, its perceptual system must generalize to the end-user's environment -- ideally without additional annotation efforts. One potential solu…