Search Results for author:
Found 6 papers, 2 papers with code
Non-Uniform Exposure Imaging via Neuromorphic Shutter Control
To address this challenge, we propose a novel Neuromorphic Shutter Control (NSC) system to avoid motion blurs and alleviate instant noises, where the extremely low latency of events is leveraged to monitor the real-time motion and facilitate the scene-adaptive exposure.
CrossZoom: Simultaneously Motion Deblurring and Event Super-Resolving
Even though the collaboration between traditional and neuromorphic event cameras brings prosperity to frame-event based vision applications, the performance is still confined by the resolution gap crossing two modalities in both spatial and temporal domains.
Learning Parallax for Stereo Event-based Motion Deblurring
To tackle this problem, we propose a novel coarse-to-fine framework, named NETwork of Event-based motion Deblurring with STereo event and intensity cameras (St-EDNet), to recover high-quality images directly from the misaligned inputs, consisting of a single blurry image and the concurrent event streams.
No-Reference Color Image Quality Assessment: From Entropy to Perceptual Quality
In the frequency domain, the two-dimensional entropy and the mutual information of the filtered sub-band images are computed as the feature set of the input color image.
A Deep Graph Embedding Network Model for Face Recognition
In this paper, we propose a new deep learning network "GENet", it combines the multi-layer network architec- ture and graph embedding framework.
Image Classification with A Deep Network Model based on Compressive Sensing
To simplify the parameter of the deep learning network, a cascaded compressive sensing model "CSNet" is implemented for image classification.
