SSL-Net: Sparse semantic learning for identifying reliable correspondences

Shunxing Chen, Guobao Xiao, Ziwei Shi, Junwen Guo, Jiayi Ma

Abstract: Highlights•We present a novel sparse semantic learning network for feature matching.•We introduce a channel-spatial attention feature gathering block to extract relevant information while suppress irrelevant context.•SSL-Net outperforms state-of-the-art methods for outlier removal and relative pose estimation.