Chia-Ming (Chris) Lee

DRCT. Accepted by New Trends in Image Restoration and Enhancement workshop (NTIRE), in conjunction with CVPR 2024.

PhaSR. PhaSR: Generalized Image Shadow Removal with Physically Aligned Priors (CVPR 2026)

ELSA. [CVPR 2026 Findings] ELSA: Exact Linear-Scan Attention for Fast and Memory-Light Vision Transformers

S3RNet. [JSTARS'26] S3RNet: Sparse Spatial--Spectral Representation with Hybrid Knowledge Distillation for Efficient Multispectral and Hyperspectral Image Fusion.

RTCS. The official pytorch implementation of "Real-Time Compressed Sensing for Joint Hyperspectral Image Transmission and Restoration for CubeSat". Accepted by IEEE Transactions on Geoscience and Remote Sensing (TGRS 2024).

GRACE. The official pytorch implementation of "GRACE: Graph-Regularized Attentive Convolutional Entanglement with Laplacian Smoothing for Robust DeepFake Video Detection". Submitted to IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI 2024).

HyFusion. The official pytorch implementation of "HyFusion: Enhanced Cross-Scale Reception Field Transformer for Hyperspectral and Multispectral Image Fusion".

E2D. Accepted by Domain adaptation, Explainability, Fairness in AI for Medical Image Analysis workshop (DEF-AI-MIA), in conjunction with CVPR 2024.

SimFlowSR. JavaScript

SMPD24. Jupyter Notebook

RACNN-pytorch. This is a third party implementation of RA-CNN in pytorch.

image-super-resolution. 🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.

AICITY_2023_Track5. Python

ncku_acvlab-smpchallenge2023. This repository is the code of our team [ncku_acvlab] used in SMP Challenge 2023.

FriedRiceLab. Official repository of the Fried Rice Lab, including code resources of the following our works: ESWT [arXiv], etc. This repository also implements many useful features and out-of-the-box image restoration models.

CMFNet. Compound Multi-branch Feature Fusion for Real Image Restoration

transformer. PyTorch Implementation of "Attention Is All You Need"

ming053l.github.io. SCSS