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Found 9 papers, 0 papers with code
Deep Hashing with Active Pairwise Supervision
n this paper, we propose a Deep Hashing method with Active Pairwise Supervision(DH-APS).
Learning Novel View Synthesis from Heterogeneous Low-light Captures
Unfortunately, synthesizing novel views remains to be a challenge for input views with heterogeneous brightness level captured under low-light condition.
3D-SceneDreamer: Text-Driven 3D-Consistent Scene Generation
Text-driven 3D scene generation techniques have made rapid progress in recent years.
Neural Invertible Variable-degree Optical Aberrations Correction
To address the issues, we propose a novel aberration correction method with an invertible architecture by leveraging its information-lossless property.
A survey on facial image deblurring
The purpose of facial image deblurring is to recover a clear image from a blurry input image, which can improve the recognition accuracy, etc.
Shap-CAM: Visual Explanations for Convolutional Neural Networks based on Shapley Value
Explaining deep convolutional neural networks has been recently drawing increasing attention since it helps to understand the networks' internal operations and why they make certain decisions.
Physics Informed Neural Fields for Smoke Reconstruction with Sparse Data
With a hybrid architecture that separates static and dynamic contents, fluid interactions with static obstacles are reconstructed for the first time without additional geometry input or human labeling.
Neural Relightable Participating Media Rendering
We propose to learn neural representations for participating media with a complete simulation of global illumination.
Learning to Importance Sample in Primary Sample Space
Importance sampling is one of the most widely used variance reduction strategies in Monte Carlo rendering.
