112 citations · 214 across the 26 of their papers we have counts for
5 papers · 1 filter
Is Out-of-Distribution Detection Learnable?
Zhen Fang, Yixuan Li, Jie Lu +3
Supervised learning aims to train a classifier under the assumption that training and test data are from the same distribution. To ease the above assumption, researchers have studi…
BoW3D: Bag of Words for Real-Time Loop Closing in 3D LiDAR SLAM
Yunge Cui, Xieyuanli Chen, Yinlong Zhang +3
Loop closing is a fundamental part of simultaneous localization and mapping (SLAM) for autonomous mobile systems. In the field of visual SLAM, bag of words (BoW) has achieved great…
LinK3D: Linear Keypoints Representation for 3D LiDAR Point Cloud
Yunge Cui, Yinlong Zhang, Jiahua Dong +3
Feature extraction and matching are the basic parts of many robotic vision tasks, such as 2D or 3D object detection, recognition, and registration. As is known, 2D feature extracti…
IDEAL: Query-Efficient Data-Free Learning from Black-box Models
Jie Zhang, Chen Chen, Lingjuan Lyu
Knowledge Distillation (KD) is a typical method for training a lightweight student model with the help of a well-trained teacher model. However, most KD methods require access to e…
Federated Class-Incremental Learning
Jiahua Dong, Lixu Wang, Zhen Fang +4
Federated learning (FL) has attracted growing attention via data-private collaborative training on decentralized clients. However, most existing methods unrealistically assume obje…