Search Results for author:
Found 8 papers, 3 papers with code
Language-guided Image Reflection Separation
This paper studies the problem of language-guided reflection separation, which aims at addressing the ill-posed reflection separation problem by introducing language descriptions to provide layer content.
Learning Event Guided High Dynamic Range Video Reconstruction
Limited by the trade-off between frame rate and exposure time when capturing moving scenes with conventional cameras, frame based HDR video reconstruction suffers from scene-dependent exposure ratio balancing and ghosting artifacts.
Coherent Event Guided Low-Light Video Enhancement
With frame-based cameras, capturing fast-moving scenes without suffering from blur often comes at the cost of low SNR and low contrast.
NeuralMPS: Non-Lambertian Multispectral Photometric Stereo via Spectral Reflectance Decomposition
In this paper, we propose a deep neural network named NeuralMPS to solve the MPS problem under general non-Lambertian spectral reflectances.
Self-Supervised Low-Light Image Enhancement Using Discrepant Untrained Network Priors
The enhancement is done by jointly optimizing the Retinex decomposition and the illumination adjustment.
Encoding Spatial Distribution of Convolutional Features for Texture Representation
Existing convolutional neural networks (CNNs) often use global average pooling (GAP) to aggregate feature maps into a single representation.
Recurrent Exposure Generation for Low-Light Face Detection
REG produces progressively and efficiently intermediate images corresponding to various exposure settings, and such pseudo-exposures are then fused by MED to detect faces across different lighting conditions.
Deep Bilateral Retinex for Low-Light Image Enhancement
Low-light images, i. e. the images captured in low-light conditions, suffer from very poor visibility caused by low contrast, color distortion and significant measurement noise.
