3 papers
cs.CV2026
Energy-Aware Imitation Learning for Steering Prediction Using Events and Frames
Hu Cao, Jiong Liu, Xingzhuo Yan +5
In autonomous driving, relying solely on frame-based cameras can lead to inaccuracies caused by factors like long exposure times, high-speed motion, and challenging lighting condit…
cs.CV2025
GLC++: Source-Free Universal Domain Adaptation through Global-Local Clustering and Contrastive Affinity Learning
Sanqing Qu, Tianpei Zou, Florian Röhrbein +4
Deep neural networks often exhibit sub-optimal performance under covariate and category shifts. Source-Free Domain Adaptation (SFDA) presents a promising solution to this dilemma,…
cs.CV2024
Embracing Events and Frames with Hierarchical Feature Refinement Network for Object Detection
Hu Cao, Zehua Zhang, Yan Xia +4
In frame-based vision, object detection faces substantial performance degradation under challenging conditions due to the limited sensing capability of conventional cameras. Event…