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 with no code
TpopT: Efficient Trainable Template Optimization on Low-Dimensional Manifolds
In this work, we study TpopT (TemPlate OPTimization) as an alternative scalable framework for detecting low-dimensional families of signals which maintains high interpretability.
ZS6D: Zero-shot 6D Object Pose Estimation using Vision Transformers
The state-of-the-art 6D object pose estimation methods rely on object-specific training and therefore do not generalize to unseen objects.
Edge Based Oriented Object Detection
In the field of remote sensing, we often utilize oriented bounding boxes (OBB) to bound the objects.
Autonomous Stabilization of Retinal Videos for Streamlining Assessment of Spontaneous Venous Pulsations
Both of the evaluations support its effectiveness in facilitating the observation of SVPs.
NeuSort: An Automatic Adaptive Spike Sorting Approach with Neuromorphic Models
NeuSort caters to the demand for real-time spike sorting in brain-machine interfaces through a neuromorphic approach.
Displacement field calculation of large-scale structures using computer vision with physical constraints
Because of the advantages of easy deployment, low cost and non-contact, computer vision-based structural displacement acquisition technique has received wide attention and research in recent years.
Image Moment Invariants to Rotational Motion Blur
Further, we achieve their invariance to similarity transform.
Pi-ViMo: Physiology-inspired Robust Vital Sign Monitoring using mmWave Radars
In this paper, we address these limitations and present "Pi-ViMo", a non-contact Physiology-inspired Robust Vital Sign Monitoring system, using mmWave radars.
You Only Crash Once: Improved Object Detection for Real-Time, Sim-to-Real Hazardous Terrain Detection and Classification for Autonomous Planetary Landings
The detection of hazardous terrain during the planetary landing of spacecraft plays a critical role in assuring vehicle safety and mission success.
LocPoseNet: Robust Location Prior for Unseen Object Pose Estimation
The prior can be used to initialize the 3D object translation and facilitate 3D object rotation estimation.
