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Found 6 papers, 3 papers with code
A Review and Efficient Implementation of Scene Graph Generation Metrics
Scene graph generation has emerged as a prominent research field in computer vision, witnessing significant advancements in the recent years.
Adapting the Segment Anything Model During Usage in Novel Situations
The interactive segmentation task consists in the creation of object segmentation masks based on user interactions.
Impact of Pseudo Depth on Open World Object Segmentation with Minimal User Guidance
In order to tell our network which object to segment, we provide the network with a single click on the object's surface on the pseudo depth map of the image as input.
All Keypoints You Need: Detecting Arbitrary Keypoints on the Body of Triple, High, and Long Jump Athletes
Performance analyses based on videos are commonly used by coaches of athletes in various sports disciplines.
Pseudo-Label Noise Suppression Techniques for Semi-Supervised Semantic Segmentation
Current SSL approaches use an initially supervised trained model to generate predictions for unlabelled images, called pseudo-labels, which are subsequently used for training a new model from scratch.
COVID Detection and Severity Prediction with 3D-ConvNeXt and Custom Pretrainings
We introduce a neural network for the prediction of the severity of lung damage and the detection of a COVID-infection using three-dimensional CT-data.
