CONSAC: Robust Multi-Model Fitting by Conditional Sample Consensus (Code @fkluger)
-
Updated
May 19, 2020 - Python
CONSAC: Robust Multi-Model Fitting by Conditional Sample Consensus (Code @fkluger)
Covering image processing and computer vision concepts with small c++ programs ranging from reading an image, histogram manipulation to object tracking.
Temporally Consistent Horizon Lines (Code @fkluger)
Deep Denoising Network in Frequency Domain for Hyperspectral Image
Source code for book "Image algorithms for low-level vision tasks" (Jia. 2024)
KITTI dataset horizon line extension proposed in the paper "Temporally Consistent Horizon Lines" (Code @fkluger)
This paper is accepted by IEEE TCSVT
low level computer vision 任务研究的一些阅读感想记录
Data Upcycling Knowledge Distillation for Image Super-Resolution (official repository)
Inference code for "Unified Multi-Weather Transformer for Multi-Weather Image Restoration".
Spatial-Spectral Quasi-Attention Recurrent Network for Hyperspectral Image Denoising.
An official source code of AAAI 2023 paper, "Robust Image Denoising of No-Flash Images Guided by Consistent Flash Images".
[AAAI'2024] DeS3: Adaptive Attention-driven Self and Soft Shadow Removal using ViT Similarity. First diffusion-based shadow removal performs robustly on hard, soft and self shadows. https://arxiv.org/abs/2211.08089
[ICME2024, Official Code] for paper "Bringing Textual Prompt to AI-Generated Image Quality Assessment"
I Can See Clearly Now : Image Restoration via De-Raining unofficial code implementation(pytorch)
Code for TIP 2017 paper --- Illumination Decomposition for Photograph with Multiple Light Sources.
[CVPRW2024, Official Code] for paper "Exploring AIGC Video Quality: A Focus on Visual Harmony, Video-Text Consistency and Domain Distribution Gap".
A Range-Null Space Decomposition Approach for Fast and Flexible Spectral Compressive Imaging
A summary of open-source deep learning-based infrared and visible image fusion and some vision algorithms.
[CVPR 2024] Color Shift Estimation-and-Correction for Image Enhancement
Add a description, image, and links to the low-level-vision topic page so that developers can more easily learn about it.
To associate your repository with the low-level-vision topic, visit your repo's landing page and select "manage topics."