36 citations · 49 across the 3 of their papers we have counts for
5 papers
UniMix: Towards Domain Adaptive and Generalizable LiDAR Semantic Segmentation in Adverse Weather
Haimei Zhao, Jing Zhang, Zhuo Chen +2
LiDAR semantic segmentation (LSS) is a critical task in autonomous driving and has achieved promising progress. However, prior LSS methods are conventionally investigated and evalu…
Data-Free Generalized Zero-Shot Learning
Bowen Tang, Long Yan, Jing Zhang +3
Deep learning models have the ability to extract rich knowledge from large-scale datasets. However, the sharing of data has become increasingly challenging due to concerns regardin…
Distortion-aware Transformer in 360° Salient Object Detection
Yinjie Zhao, Lichen Zhao, Qian Yu +3
With the emergence of VR and AR, 360° data attracts increasing attention from the computer vision and multimedia communities. Typically, 360° data is projected into 2D ERP (equirec…
GETAM: Gradient-weighted Element-wise Transformer Attention Map for Weakly-supervised Semantic segmentation
Weixuan Sun, Jing Zhang, Zheyuan Liu +2
Weakly Supervised Semantic Segmentation (WSSS) is challenging, particularly when image-level labels are used to supervise pixel level prediction. To bridge their gap, a Class Activ…
Deep Convolutional Neural Networks for Action Recognition Using Depth Map Sequences
Pichao Wang, Wanqing Li, Zhimin Gao +3
Recently, deep learning approach has achieved promising results in various fields of computer vision. In this paper, a new framework called Hierarchical Depth Motion Maps (HDMM) +…