2 citations · 3 across the 4 of their papers we have counts for
9 papers · 1 filter
Watch Where You Move: Region-aware Dynamic Aggregation and Excitation for Gait Recognition
Binyuan Huang, Yongdong Luo, Xianda Guo +4
Deep learning-based gait recognition has achieved great success in various applications. The key to accurate gait recognition lies in considering the unique and diverse behavior pa…
TUNI: Unifying Pre-training and Fine-tuning with Modality-Aware Mutual Learning and Rectification for RGB-T Semantic Segmentation
Xiaodong Guo, Xianda Guo, Tong Liu +4
RGB-thermal (RGB-T) semantic segmentation improves the environmental perception of autonomous platforms in challenging conditions. Prevailing RGB-T segmentation frameworks suffer f…
MaskFuser: Masked Fusion of Joint Multi-Modal Tokenization for End-to-End Autonomous Driving
Yiqun Duan, Xianda Guo, Zheng Zhu +3
Current multi-modality driving frameworks normally fuse representation by utilizing attention between single-modality branches. However, the existing networks still suppress the dr…
OpenStereo: A Comprehensive Benchmark for Stereo Matching and Strong Baseline
Xianda Guo, Chenming Zhang, Juntao Lu +5
Stereo matching aims to estimate the disparity between matching pixels in a stereo image pair, which is important to robotics, autonomous driving, and other computer vision tasks.…
Multi-Prompt with Depth Partitioned Cross-Modal Learning
Yingjie Tian, Yiqi Wang, Xianda Guo +2
In recent years, soft prompt learning methods have been proposed to fine-tune large-scale vision-language pre-trained models for various downstream tasks. These methods typically c…
CompletionFormer: Depth Completion with Convolutions and Vision Transformers
Zhang Youmin, Guo Xianda, Poggi Matteo +3
Given sparse depths and the corresponding RGB images, depth completion aims at spatially propagating the sparse measurements throughout the whole image to get a dense depth predict…