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Found 6 papers, 3 papers with code
Just Add $100 More: Augmenting NeRF-based Pseudo-LiDAR Point Cloud for Resolving Class-imbalance Problem
Typical LiDAR-based 3D object detection models are trained in a supervised manner with real-world data collection, which is often imbalanced over classes (or long-tailed).
Combating the Instability of Mutual Information-based Losses via Regularization
Notable progress has been made in numerous fields of machine learning based on neural network-driven mutual information (MI) bounds.
Painting Outside as Inside: Edge Guided Image Outpainting via Bidirectional Rearrangement with Progressive Step Learning
The bidirectional boundary region rearrangement enables the generation of the missing region using bidirectional information similar to that of the image inpainting task, thereby generating the higher quality than the conventional methods using unidirectional information.
End-to-End Differentiable Learning to HDR Image Synthesis for Multi-exposure Images
We tackle the problem in stack reconstruction-based methods by proposing a novel framework with a fully differentiable high dynamic range imaging (HDRI) process.
Deep Recursive HDRI: Inverse Tone Mapping using Generative Adversarial Networks
Because most images have a low dynamic range, recovering the lost dynamic range from a single low dynamic range image is still prevalent.
Deep Chain HDRI: Reconstructing a High Dynamic Range Image from a Single Low Dynamic Range Image
The proposed model is based on a convolutional neural network composed of dilated convolutional layers, and infers LDR images with various exposures and illumination from a single LDR image of the same scene.
