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Found 7 papers, 4 papers with code
INT: Towards Infinite-frames 3D Detection with An Efficient Framework
By employing INT on CenterPoint, we can get around 7% (Waymo) and 15% (nuScenes) performance boost with only 2~4ms latency overhead, and currently SOTA on the Waymo 3D Detection leaderboard.
LSEC: Large-scale spectral ensemble clustering
In LSEC, a large-scale spectral clustering based efficient ensemble generation framework is designed to generate various base clusterings within a low computational complexity.
Divide-and-conquer based Large-Scale Spectral Clustering
In this paper, we propose a divide-and-conquer based large-scale spectral clustering method to strike a good balance between efficiency and effectiveness.
Ranked #2 on
Image/Document Clustering
on pendigits
Ensemble Learning for Spectral Clustering
Instead of directly using the clustering results obtained from each base spectral clustering algorithm, the proposed method learns a robust presentation of graph Laplacian by ensemble learning from the spectral embedding of each base spectral clustering algorithm.
Ranked #1 on
Image/Document Clustering
on Wine
Robust event-stream pattern tracking based on correlative filter
Object tracking based on retina-inspired and event-based dynamic vision sensor (DVS) is challenging for the noise events, rapid change of event-stream shape, chaos of complex background textures, and occlusion.
Super-resolution of spatiotemporal event-stream image captured by the asynchronous temporal contrast vision sensor
Firstly, the event number of each pixel of the HR DVS image is determined with a sparse signal representation based method to obtain the HR event-count map from that of the LR DVS recording.
Real-time Tracking Based on Neuromrophic Vision
Neuromorphic vision is a concept defined by incorporating neuromorphic vision sensors such as silicon retinas in vision processing system.
