Template Matching
57 papers with code • 0 benchmarks • 0 datasets
Template matching is a technique that is used to find a subimage or a patch (called the template) within a larger image. The basic idea behind template matching is to slide the template image over the larger image and compare the template to each portion of the larger image to determine the similarity between the template and the corresponding portion of the larger image.
Benchmarks
These leaderboards are used to track progress in Template Matching
Latest papers
Quantifying the Resolution of a Template after Image Registration
Stochastik-TU-Ilmenau/image-template-resolution
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In many image processing applications (e. g. computational anatomy) a groupwise registration is performed on a sample of images and a template image is simultaneously generated.
ARTrackV2: Prompting Autoregressive Tracker Where to Look and How to Describe
miv-xjtu/artrack
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We present ARTrackV2, which integrates two pivotal aspects of tracking: determining where to look (localization) and how to describe (appearance analysis) the target object across video frames.
Thoracic Cartilage Ultrasound-CT Registration using Dense Skeleton Graph
To address this challenge, a graph-based non-rigid registration is proposed to enable transferring planned paths from the atlas to the current setup by explicitly considering subcutaneous bone surface features instead of the skin surface.
Efficient High-Resolution Template Matching with Vector Quantized Nearest Neighbour Fields
aktgpt/vq-nnf
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A vector quantization step is introduced before the NN calculation to represent the template with $k$ features, and the filter response over the NNFs is used to compare the template and query distributions over the features.
L2V2T2Calib: Automatic and Unified Extrinsic Calibration Toolbox for Different 3D LiDAR, Visual Camera and Thermal Camera
To unify the process, an important step is to automatically and robustly detect the target from different types of LiDARs.
Self-supervised Vision Transformers for 3D Pose Estimation of Novel Objects
sthalham/tram3d
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This work evaluates and demonstrates the differences between self-supervised CNNs and Vision Transformers for deep template matching.
Evaluation of a Canonical Image Representation for Sidescan Sonar
In this paper, a canonical transformation method consisting of intensity correction and slant range correction is proposed to decrease the above distortion.
DoUnseen: Tuning-Free Class-Adaptive Object Detection of Unseen Objects for Robotic Grasping
AnasIbrahim/image_agnostic_segmentation
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In this work, we are interested in open sets where the number of classes is unknown, varying, and without pre-knowledge about the objects' types.
Learning Accurate Template Matching with Differentiable Coarse-to-Fine Correspondence Refinement
zhirui-gao/deep-template-matching
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To tackle the challenges, we propose an accurate template matching method based on differentiable coarse-to-fine correspondence refinement.
Nonlinear Intensity, Scale and Rotation Invariant Matching for Multimodal Images
We present an effective method for the matching of multimodal images.
