Key Point Matching
10 papers with code • 0 benchmarks • 3 datasets
Given a debatable topic, a set of key points per stance, and a set of crowd arguments supporting or contesting the topic, report for each argument its match score for each of the key points under the same stance towards the topic.
Benchmarks
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Libraries
Use these libraries to find Key Point Matching models and implementations
ArgKP-2021
FewSOL
Most implemented papers
AdaLAM: Revisiting Handcrafted Outlier Detection
Local feature matching is a critical component of many computer vision pipelines, including among others Structure-from-Motion, SLAM, and Visual Localization.
Quantitative Argument Summarization and Beyond: Cross-Domain Key Point Analysis
Recent work has proposed to summarize arguments by mapping them to a small set of expert-generated key points, where the salience of each key point corresponds to the number of its matching arguments.
LightGlue: Local Feature Matching at Light Speed
We introduce LightGlue, a deep neural network that learns to match local features across images.
Probabilistic Inference for Camera Calibration in Light Microscopy under Circular Motion
Robust and accurate camera calibration is essential for 3D reconstruction in light microscopy under circular motion.
Team Enigma at ArgMining-EMNLP 2021: Leveraging Pre-trained Language Models for Key Point Matching
manavkapadnis/enigma_argmining
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EMNLP (ArgMining) 2021
We present the system description for our submission towards the Key Point Analysis Shared Task at ArgMining 2021.
ENRICH: Multi-purposE dataset for beNchmaRking In Computer vision and pHotogrammetry
The availability of high-resolution data and accurate ground truth is essential to evaluate and compare methods and algorithms properly.
RoMa: Robust Dense Feature Matching
parskatt/roma
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The aim is to learn a robust model, i. e., a model able to match under challenging real-world changes.
Stable Remaster: Bridging the Gap Between Old Content and New Displays
We explore the ability to combine multiple independent computer vision tasks to attempt to solve the problem of expanding aspect ratios of old animated content such that the new content would be indistinguishable from the source material to a brand-new viewer.
DeDoDe v2: Analyzing and Improving the DeDoDe Keypoint Detector
parskatt/dedode
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First, we find that DeDoDe keypoints tend to cluster together, which we fix by performing non-max suppression on the target distribution of the detector during training.
