6 papers
DASH: 4D Hash Encoding with Self-Supervised Decomposition for Real-Time Dynamic Scene Rendering
Jie Chen, Zhangchi Hu, Peixi Wu +3
Dynamic scene reconstruction is a long-term challenge in 3D vision. Existing plane-based methods in dynamic Gaussian splatting suffer from an unsuitable low-rank assumption, causin…
Efficient Event-Based Semantic Segmentation via Exploiting Frame-Event Fusion: A Hybrid Neural Network Approach
Hebei Li, Yansong Peng, Jiahui Yuan +4
Event cameras have recently been introduced into image semantic segmentation, owing to their high temporal resolution and other advantageous properties. However, existing event-bas…
Dome-DETR: DETR with Density-Oriented Feature-Query Manipulation for Efficient Tiny Object Detection
Zhangchi Hu, Peixi Wu, Jie Chen +5
Tiny object detection plays a vital role in drone surveillance, remote sensing, and autonomous systems, enabling the identification of small targets across vast landscapes. However…
Efficient Spiking Point Mamba for Point Cloud Analysis
Peixi Wu, Bosong Chai, Menghua Zheng +6
Bio-inspired Spiking Neural Networks (SNNs) provide an energy-efficient way to extract 3D spatio-temporal features. However, existing 3D SNNs have struggled with long-range depende…
Spiking Point Transformer for Point Cloud Classification
Peixi Wu, Bosong Chai, Hebei Li +6
Spiking Neural Networks (SNNs) offer an attractive and energy-efficient alternative to conventional Artificial Neural Networks (ANNs) due to their sparse binary activation. When SN…
D-FINE: Redefine Regression Task in DETRs as Fine-grained Distribution Refinement
Yansong Peng, Hebei Li, Peixi Wu +3
We introduce D-FINE, a powerful real-time object detector that achieves outstanding localization precision by redefining the bounding box regression task in DETR models. D-FINE com…