[AAAI‘ 2025 ] "AGLLDiff: Guiding Diffusion Models Towards Unsupervised Training-free Real-world Low-light Image Enhancement".

No fortress, purely open ground. OpenManus is Coming.

Grounded SAM 2: Ground and Track Anything in Videos with Grounding DINO, Florence-2 and SAM 2

[ECCV 2024] Official implementation of the paper "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection"

Efficient Track Anything

[NeurIPS 2023] Global Structure-Aware Diffusion Process for Low-Light Image Enhancement

The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use th…

This is the official code of “Enhancing Nighttime UAV Tracking with Light Distribution Suppression”.

Exploring Richer and More Accurate Information via Frequency Selection for Image Restoration

This is the official code for the paper "SAM-DA: UAV Tracks Anything at Night with SAM-Powered Domain Adaptation".

Official Implementation of ECCV2024 paper: SLAck

Official pytorch implementation for "LightenDiffusion: Unsupervised Low-Light Image Enhancement with Latent-Retinex Diffusion Models"

This is the official implementation of YOLA, NeurIPS2024

[ECCV 2024] This is the official code for the paper "Fast Context-Based Low-Light Image Enhancement via Neural Implicit Representations"

Official PyTorch implementation of "Temporal As a Plugin: Unsupervised Video Denoising with Pre-Trained Image Denoisers" in ECCV 2024.

Official repository of "SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory"