sgawalsh/stvNet
6D pose-estimation model and algorithm based on pvNet
stvNet helps industrial automation or quality control professionals accurately determine the 3D position and orientation of an object from a standard camera image. It takes an RGB image of a scene containing the object and outputs its precise 6D pose (translation and rotation) relative to the camera. This is for engineers and technicians who need to track or manipulate objects in space without specialized depth sensors.
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Use this if you need to precisely locate specific objects in 3D space using only a single 2D camera image for applications like robotic grasping or augmented reality overlays.
Not ideal if your application requires real-time 6D pose estimation at very high frame rates or if you already have depth data available from sensors like LiDAR or structured light.
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Last pushed
Jul 29, 2025
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