4 citations · 17 across the 13 of their papers we have counts for
13 papers
DriveWorld: 4D Pre-trained Scene Understanding via World Models for Autonomous Driving
Chen Min, Dawei Zhao, Liang Xiao +10
Vision-centric autonomous driving has recently raised wide attention due to its lower cost. Pre-training is essential for extracting a universal representation. However, current vi…
Density-guided Translator Boosts Synthetic-to-Real Unsupervised Domain Adaptive Segmentation of 3D Point Clouds
Zhimin Yuan, Wankang Zeng, Yanfei Su +4
3D synthetic-to-real unsupervised domain adaptive segmentation is crucial to annotating new domains. Self-training is a competitive approach for this task, but its performance is l…
Point Contrastive Prediction with Semantic Clustering for Self-Supervised Learning on Point Cloud Videos
Xiaoxiao Sheng, Zhiqiang Shen, Gang Xiao +3
We propose a unified point cloud video self-supervised learning framework for object-centric and scene-centric data. Previous methods commonly conduct representation learning at th…
GeoTransformer: Fast and Robust Point Cloud Registration with Geometric Transformer
Zheng Qin, Hao Yu, Changjian Wang +5
We study the problem of extracting accurate correspondences for point cloud registration. Recent keypoint-free methods have shown great potential through bypassing the detection of…
Variational Probabilistic Fusion Network for RGB-T Semantic Segmentation
Baihong Lin, Zengrong Lin, Yulan Guo +3
RGB-T semantic segmentation has been widely adopted to handle hard scenes with poor lighting conditions by fusing different modality features of RGB and thermal images. Existing me…
PointCMP: Contrastive Mask Prediction for Self-supervised Learning on Point Cloud Videos
Zhiqiang Shen, Xiaoxiao Sheng, Longguang Wang +3
Self-supervised learning can extract representations of good quality from solely unlabeled data, which is appealing for point cloud videos due to their high labelling cost. In this…