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Zero-shot Compound Expression Recognition with Visual Language Model at the 6th ABAW Challenge
Conventional approaches to facial expression recognition primarily focus on the classification of six basic facial expressions.
Joint Prediction of Monocular Depth and Structure using Planar and Parallax Geometry
Supervised learning depth estimation methods can achieve good performance when trained on high-quality ground-truth, like LiDAR data.
Plug-and-play Shape Refinement Framework for Multi-site and Lifespan Brain Skull Stripping
For instance, the model trained on a dataset with specific imaging parameters cannot be well applied to other datasets with different imaging parameters.
An Empirical Comparison of Unsupervised Constituency Parsing Methods
Unsupervised constituency parsing aims to learn a constituency parser from a training corpus without parse tree annotations.
Leveraging Uncertainties for Deep Multi-modal Object Detection in Autonomous Driving
This work presents a probabilistic deep neural network that combines LiDAR point clouds and RGB camera images for robust, accurate 3D object detection.
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