Abstract: 6D object pose estimation is a fundamental yet challenging problem in computer vision. Convolutional Neural Networks (CNNs) have recently proven to be capable of predicting reliable 6D pose ...
Most recent 6D object pose estimation methods first use object detection to obtain 2D bounding boxes before actually regressing the pose. However, the general object detection methods they use are ill ...
You can download the pretrained models for detection and keypoint detection. Please place the models as follows. We also put the test images for the LMO dataset in ...
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Abstract: Zero-shot 6D object pose estimation involves the detection of novel objects with their 6D poses in cluttered scenes, presenting significant challenges for model generalizability. Fortunately ...
±3 (2, 3, 5, 7 frames at 1/3 EV, 1/2 EV steps) ±2 (3 frames at 1/3 EV, 1/2 EV steps) Yes (3 frames in either blue/amber or magenta/green axis) Yes (3 frames in either blue/amber or magenta/green axis) ...
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