Attention Guided Low-light Image Enhancement with a Large Scale Low-light Simulation Dataset, IJCV 2021.

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

GenISP: Neural ISP for Low-Light Machine Cognition

🌕 [ICCV 2021] Multitask AET with Orthogonal Tangent Regularity for Dark Object Detection. A self-supervised learning way for low-light image object detection.

[Access 2020] Low-Light Image Enhancement With Regularized Illumination Optimization and Deep Noise Suppression

"Retinexformer: One-stage Retinex-based Transformer for Low-light Image Enhancement" (ICCV 2023) & (NTIRE 2024 Challenge)

[ICCV 2023] FeatEnHancer: Enhancing Hierarchical Features for Object Detection and Beyond Under Low-Light Vision

🌕 [AAAI 2024] Aleth-NeRF: Illumination Adaptive NeRF with Concealing Field Assumption (Low-light enhance / Exposure correction + NeRF)

[TCSVT'22] Enlightening Low-Light Images With Dynamic Guidance for Context Enrichment

LYT-Net: Lightweight YUV Transformer-based Network for Low-Light Image Enhancement

[ECCV'24] Unrolled Decomposed Unpaired Learning for Controllable Low-Light Video Enhancement

This repository contains a Python-based program that detects and tracks people in a video, counting the number of individuals entering and exiting a defined area. It uses the YOLOv8 model for object detection and the SORT (Simple Online and Realtime Tracking) algorithm for tracking.