191 citations · 207 across the 7 of their papers we have counts for
7 papers
RelBench: A Benchmark for Deep Learning on Relational Databases
Joshua Robinson, Rishabh Ranjan, Weihua Hu +9
We present RelBench, a public benchmark for solving predictive tasks over relational databases with graph neural networks. RelBench provides databases and tasks spanning diverse do…
LION: Linear Group RNN for 3D Object Detection in Point Clouds
Zhe Liu, Jinghua Hou, Xinyu Wang +4
The benefit of transformers in large-scale 3D point cloud perception tasks, such as 3D object detection, is limited by their quadratic computation cost when modeling long-range rel…
Anomaly Detection by Adapting a pre-trained Vision Language Model
Yuxuan Cai, Xinwei He, Dingkang Liang +2
Recently, large vision and language models have shown their success when adapting them to many downstream tasks. In this paper, we present a unified framework named CLIP-ADA for An…
An open dataset for the evolution of oracle bone characters: EVOBC
Haisu Guan, Jinpeng Wan, Yuliang Liu +6
The earliest extant Chinese characters originate from oracle bone inscriptions, which are closely related to other East Asian languages. These inscriptions hold immense value for a…
A Discrepancy Aware Framework for Robust Anomaly Detection
Yuxuan Cai, Dingkang Liang, Dongliang Luo +3
Defect detection is a critical research area in artificial intelligence. Recently, synthetic data-based self-supervised learning has shown great potential on this task. Although ma…
StereoDistill: Pick the Cream from LiDAR for Distilling Stereo-based 3D Object Detection
Zhe Liu, Xiaoqing Ye, Xiao Tan +2
In this paper, we propose a cross-modal distillation method named StereoDistill to narrow the gap between the stereo and LiDAR-based approaches via distilling the stereo detectors…