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Found 8 papers, 3 papers with code
Are metrics measuring what they should? An evaluation of image captioning task metrics
Looking to measure how well or not the set of current and more recent metrics are doing, in this article, we present an evaluation of several kinds of Image Captioning metrics and a comparison between them using the well-known MS COCO dataset.
Video Captioning: a comparative review of where we are and which could be the route
As a result, the most-used datasets and metrics are identified.
Similarity search on neighbor's graphs with automatic Pareto optimal performance and minimum expected quality setups based on hyperparameter optimization
This manuscript introduces an autotuned algorithm for searching nearest neighbors based on neighbor graphs and optimization metaheuristics to produce Pareto-optimal searches for quality and search speed automatically; the same strategy is also used to produce indexes that achieve a minimum quality.
Regionalized models for Spanish language variations based on Twitter
Spanish is one of the most spoken languages in the globe, but not necessarily Spanish is written and spoken in the same way in different countries.
Infotec + CentroGEO at SemEval-2020 Task 8: Deep Learning and Text Categorization approach for Memes classification
We obtained results analyzing the text and images separately, and also in combination.
Hyperparameter-Free Losses for Model-Based Monocular Reconstruction
This work proposes novel hyperparameter-free losses for single view 3D reconstruction with morphable models (3DMM).
A scalable solution to the nearest neighbor search problem through local-search methods on neighbor graphs
Near neighbor search (NNS) is a powerful abstraction for data access; however, data indexing is troublesome even for approximate indexes.
Proximal Navigation Graphs and t-spanners
We call $G$ a {\em proximal navigation graph} or $PN$-graph if for each edge $(u, v) \in E$ either $u=v$ or there is a node $u_1$ such that $(u, u_1) \in E$ and $\mathbf{d}(u, v) > \mathbf{d}(u_1, v)$.
Computational Geometry
