text: 406,74,1253247752848519171,841031248839618560,Relja Arandjelović,"New paper by my student Ignacio Rocco - a 10x faster and less memory hungry NCNet with equivalent results (or more accurate with a smaller speedup) <LINK> . Code and models available <LINK> <LINK> @ducha_aiki You mean to the challenge? I'll mention it but I'm not sure we have the time (NeurIPS, personal reasons, etc)",https://arxiv.org/abs/2004.10566,"In this work we target the problem of estimating accurately localised correspondences between a pair of images. We adopt the recent Neighbourhood Consensus Networks that have demonstrated promising performance for difficult correspondence problems and propose modifications to overcome their main limitations: large memory consumption, large inference time and poorly localised correspondences. Our proposed modifications can reduce the memory footprint and execution time more than $10\times$, with equivalent results. This is achieved by sparsifying the correlation tensor containing tentative matches, and its subsequent processing with a 4D CNN using submanifold sparse convolutions. Localisation accuracy is significantly improved by processing the input images in higher resolution, which is possible due to the reduced memory footprint, and by a novel two-stage correspondence relocalisation module. The proposed Sparse-NCNet method obtains state-of-the-art results on the HPatches Sequences and InLoc visual localisation benchmarks, and competitive results in the Aachen Day-Night benchmark. ","Efficient Neighbourhood Consensus Networks via Submanifold Sparse