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Found 6 papers, 3 papers with code
TransCDR: a deep learning model for enhancing the generalizability of cancer drug response prediction through transfer learning and multimodal data fusion for drug representation
Although many models have been developed to utilize the representations of drugs and cancer cell lines for predicting cancer drug responses (CDR), their performances can be improved by addressing issues such as insufficient data modality, suboptimal fusion algorithms, and poor generalizability for novel drugs or cell lines.
For A More Comprehensive Evaluation of 6DoF Object Pose Tracking
The limitations of previous scoring methods and error metrics are analyzed, based on which we introduce our improved evaluation methods.
Guided Linear Upsampling
We demonstrate the advantages of our method for both interactive image editing and real-time high-resolution video processing.
Large-displacement 3D Object Tracking with Hybrid Non-local Optimization
Optimization-based 3D object tracking is known to be precise and fast, but sensitive to large inter-frame displacements.
BCOT: A Markerless High-Precision 3D Object Tracking Benchmark
Our new benchmark dataset contains 20 textureless objects, 22 scenes, 404 video sequences and 126K images captured in real scenes.
Sparsely Grouped Multi-task Generative Adversarial Networks for Facial Attribute Manipulation
To overcome such a key limitation, we propose Sparsely Grouped Generative Adversarial Networks (SG-GAN) as a novel approach that can translate images on sparsely grouped datasets where only a few samples for training are labelled.
