54 citations · 77 across the 8 of their papers we have counts for
5 papers · 1 filter
Pre-Training LiDAR-Based 3D Object Detectors Through Colorization
Tai-Yu Pan, Chenyang Ma, Tianle Chen +7
Accurate 3D object detection and understanding for self-driving cars heavily relies on LiDAR point clouds, necessitating large amounts of labeled data to train. In this work, we in…
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…
Emergent Correspondence from Image Diffusion
Luming Tang, Menglin Jia, Qianqian Wang +2
Finding correspondences between images is a fundamental problem in computer vision. In this paper, we show that correspondence emerges in image diffusion models without any explici…
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…
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…