Heitor Rapela Medeiros's repositories
the-algorithm
Source code for Twitter's Recommendation Algorithm
AnimateDiff
Official implementation of AnimateDiff.
Anti-UAV
🔥🔥Official Repository for Anti-UAV🔥🔥
Awesome-RGBT-Feature-Fusion
A collection of RGB-T-Feature-Fusion methods (deep learning methods mainly), codes, and datasets. The main directions involved are Multispectral Pedestrian, RGB-T Vehicle Detection, RGB-T Crowd Counting, RGB-T Fusion Tracking.
awesome-source-free-test-time-adaptation
A curated list of papers in Test-time Adaptation, Test-time Training and Source-free Domain Adaptation
binary-latent-diffusion
Implementation of Binary Latent Diffusion
ControlNet
Let us control diffusion models
ControlVideo
Official pytorch implementation of "ControlVideo: Training-free Controllable Text-to-Video Generation"
Crowd_counting_from_scratch
This is an overview and tutorial about crowd counting. In this repository, you can learn how to estimate number of pedestrians in crowd scenes through computer vision and deep learning.
cs-video-courses
List of Computer Science courses with video lectures.
dropout
Code release for "Dropout Reduces Underfitting"
FastSAM
Fast Segment Anything
Gen-L-Video
The official implementation for "Gen-L-Video: Multi-Text to Long Video Generation via Temporal Co-Denoising".
ImageBind
ImageBind One Embedding Space to Bind Them All
med-seg-diff-pytorch
Implementation of MedSegDiff in Pytorch - SOTA medical segmentation using DDPM and filtering of features in fourier space
ml-fastvit
This repository contains the official implementation of the research paper, "FastViT: A Fast Hybrid Vision Transformer using Structural Reparameterization"
OneDiffusion
OneDiffusion: Run any Stable Diffusion models and fine-tuned weights with ease
stable-diffusion-webui-colab
stable diffusion webui colab
SwinFusion
This is official Pytorch implementation of "SwinFusion: Cross-domain Long-range Learning for General Image Fusion via Swin Transformer"
T2I-Adapter
T2I-Adapter
tiny-diffusion
A minimal PyTorch implementation of probabilistic diffusion models for 2D datasets.