2 citations · 3 across the 6 of their papers we have counts for
6 papers
MS2Edge: Towards Energy-Efficient and Crisp Edge Detection with Multi-Scale Residual Learning in SNNs
Yimeng Fan, Changsong Liu, Mingyang Li +3
Edge detection with Artificial Neural Networks (ANNs) has achieved remarkable prog\-ress but faces two major challenges. First, it requires pre-training on large-scale extra data a…
Image-Plane Geometric Decoding for View-Invariant Indoor Scene Reconstruction
Mingyang Li, Yimeng Fan, Changsong Liu +4
Volume-based indoor scene reconstruction methods offer superior generalization capability and real-time deployment potential. However, existing methods rely on multi-view pixel bac…
SpikeDet: Better Firing Patterns for Accurate and Energy-Efficient Object Detection with Spiking Neural Networks
Yimeng Fan, Changsong Liu, Mingyang Li +4
Spiking Neural Networks (SNNs) are the third generation of neural networks. They have gained widespread attention in object detection due to their low energy consumption and biolog…
Cycle Pixel Difference Network for Crisp Edge Detection
Changsong Liu, Wei Zhang, Yanyan Liu +5
Edge detection, as a fundamental task in computer vision, has garnered increasing attention. The advent of deep learning has significantly advanced this field. However, recent deep…
Learning to utilize image second-order derivative information for crisp edge detection
Changsong Liu, Yimeng Fan, Mingyang Li +5
Edge detection is a fundamental task in computer vision. It has made great progress under the development of deep convolutional neural networks (DCNNs), some of which have achieved…
SFOD: Spiking Fusion Object Detector
Yimeng Fan, Wei Zhang, Changsong Liu +2
Event cameras, characterized by high temporal resolution, high dynamic range, low power consumption, and high pixel bandwidth, offer unique capabilities for object detection in spe…