5 papers
Weaving Light and Time: Unified Harmonic-Geometric Representation Learning for Dense RGB-Event Parsing
Chenxu Peng, Chongtian zhou, Dicheng Liu +5
Fusing standard RGB frames with asynchronous event streams has emerged as a definitive paradigm for robust perception in degraded environments. Although unified backbones have rece…
Enhancing Representations through Heterogeneous Self-Supervised Learning
Zhong-Yu Li, Bo-Wen Yin, Yongxiang Liu +2
Incorporating heterogeneous representations from different architectures has facilitated various vision tasks, e.g., some hybrid networks combine transformers and convolutions. How…
OmniSegmentor: A Flexible Multi-Modal Learning Framework for Semantic Segmentation
Bo-Wen Yin, Jiao-Long Cao, Xuying Zhang +3
Recent research on representation learning has proved the merits of multi-modal clues for robust semantic segmentation. Nevertheless, a flexible pretrain-and-finetune pipeline for…
DFormerv2: Geometry Self-Attention for RGBD Semantic Segmentation
Bo-Wen Yin, Jiao-Long Cao, Ming-Ming Cheng +1
Recent advances in scene understanding benefit a lot from depth maps because of the 3D geometry information, especially in complex conditions (e.g., low light and overexposed). Exi…
Multi-Token Enhancing for Vision Representation Learning
Zhong-Yu Li, Yu-Song Hu, Bo-Wen Yin +1
Vision representation learning, especially self-supervised learning, is pivotal for various vision applications. Ensemble learning has also succeeded in enhancing the performance a…