most citedUniG-Encoder: A Universal Feature Encoder for Graph and Hypergraph Node Classification

38 citations · 42 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2024

HGS-Mapping: Online Dense Mapping Using Hybrid Gaussian Representation in Urban Scenes

Ke Wu, Kaizhao Zhang, Zhiwei Zhang +7

Online dense mapping of urban scenes forms a fundamental cornerstone for scene understanding and navigation of autonomous vehicles. Recent advancements in mapping methods are mainl…

cs.CV20231 cited

OpenAnnotate3D: Open-Vocabulary Auto-Labeling System for Multi-modal 3D Data

Yijie Zhou, Likun Cai, Xianhui Cheng +3

In the era of big data and large models, automatic annotating functions for multi-modal data are of great significance for real-world AI-driven applications, such as autonomous dri…

cs.LG202338 cited

UniG-Encoder: A Universal Feature Encoder for Graph and Hypergraph Node Classification

Minhao Zou, Zhongxue Gan, Yutong Wang +4

Graph and hypergraph representation learning has attracted increasing attention from various research fields. Despite the decent performance and fruitful applications of Graph Neur…

cs.CV20232 cited

Improving Generalization in Visual Reinforcement Learning via Conflict-aware Gradient Agreement Augmentation

Siao Liu, Zhaoyu Chen, Yang Liu +8

Learning a policy with great generalization to unseen environments remains challenging but critical in visual reinforcement learning. Despite the success of augmentation combinatio…

cs.AI20231 cited

Adversarial Amendment is the Only Force Capable of Transforming an Enemy into a Friend

Chong Yu, Tao Chen, Zhongxue Gan

Adversarial attack is commonly regarded as a huge threat to neural networks because of misleading behavior. This paper presents an opposite perspective: adversarial attacks can be…

cs.CV2023

Boost Vision Transformer with GPU-Friendly Sparsity and Quantization

Chong Yu, Tao Chen, Zhongxue Gan +1

The transformer extends its success from the language to the vision domain. Because of the stacked self-attention and cross-attention blocks, the acceleration deployment of vision…