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scott's Projects

lpnet-pytorch icon lpnet-pytorch

This repository is a PyTorch version of the paper "Luminance-aware Pyramid Network for Low-light Image Enhancement" (TMM 2020).

lptn icon lptn

Official implementation of the paper 'High-Resolution Photorealistic Image Translation in Real-Time: A Laplacian Pyramid Translation Network' in CVPR 2021

lrd icon lrd

Official implementation for our ICCV 2023 paper “Towards General Low-Light Raw Noise Synthesis and Modeling”

lrdunet icon lrdunet

U-Net based neural network for fringe pattern denoising

lsps icon lsps

Source code for "3D Hand Pose Estimation using Simulation and Partial-Supervision with a Shared Latent Space"

lvenet icon lvenet

This is the python code corresponding to the article "Lightweight Deep Network-Enabled Real-Time Low-Visibility Enhancement for Promoting Vessel Detection in Maritime Video Surveillance"

lvlm-lp icon lvlm-lp

The First to Know: How Token Distributions Reveal Hidden Knowledge in Large Vision-Language Models?

maad-face icon maad-face

A face database with a large number of high-quality attribute annotations

madtp icon madtp

MADTP: Multimodal Alignment-Guided Dynamic Token Pruning for Accelerating Vision-Language Transformer

mantis icon mantis

Official code for Paper "Mantis: Multi-Image Instruction Tuning"

mardn icon mardn

Multi-resolution Space-attended Residual Dense Network for Single Image Super-Resolution

mbllen icon mbllen

Code for “MBLLEN: Low-light Image/Video Enhancement Using CNNs”, BMVC 2018.

mdranet icon mdranet

MDRANet: A multiscale dense residual attention network for multimodal anatomical and functional medical image fusion

meal-v2 icon meal-v2

MEAL V2: Boosting Vanilla ResNet-50 to 80%+ Top-1 Accuracy on ImageNet without Tricks

metricnet icon metricnet

Online Filtering Training Samples for Robust Visual Tracking (ACM MM2020)

mimo-unet icon mimo-unet

MIMO-UNet - Official Pytorch Implementation

mirnetv2 icon mirnetv2

[TPAMI 2022] Learning Enriched Features for Fast Image Restoration and Enhancement. Results on Defocus Deblurring, Denoising, Super-resolution, and image enhancement

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