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Mario Malave's Projects

3d-ken-burns icon 3d-ken-burns

an implementation of 3D Ken Burns Effect from a Single Image using PyTorch

basicsr icon basicsr

Open Source Image and Video Restoration Toolbox for Super-resolution, Denoise, Deblurring, etc. Currently, it includes EDSR, RCAN, SRResNet, SRGAN, ESRGAN, EDVR, etc. Also support StyleGAN2, DFDNet.

c3d icon c3d

C3D is a modified version of BVLC caffe to support 3D ConvNets.

codeformer icon codeformer

[NeurIPS 2022] Towards Robust Blind Face Restoration with Codebook Lookup Transformer

deep-search icon deep-search

Deep learning-powered search service to find segments of videos

demo-self-driving icon demo-self-driving

Streamlit app demonstrating an image browser for the Udacity self-driving-car dataset with realtime object detection using YOLO.

densecap-1 icon densecap-1

Dense captioning with joint inference and visual context

densecap4rank icon densecap4rank

In this project, dense captioning is used to index/rank videos.

densevideocaptioning icon densevideocaptioning

Official Tensorflow Implementation of the paper "Bidirectional Attentive Fusion with Context Gating for Dense Video Captioning" in CVPR 2018, with code, model and prediction results.

draggan icon draggan

Official Code for DragGAN (SIGGRAPH 2023)

gfpgan icon gfpgan

GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.

imagestackalignator icon imagestackalignator

Implementation of Google's Handheld Multi-Frame Super-Resolution algorithm (from Pixel 3 and Pixel 4 camera)

mat icon mat

MAT: Mask-Aware Transformer for Large Hole Image Inpainting

mediapipe icon mediapipe

MediaPipe is a cross-platform framework for building multimodal applied machine learning pipelines

mingpt icon mingpt

A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training

minigpt-4 icon minigpt-4

MiniGPT-4: Enhancing Vision-language Understanding with Advanced Large Language Models

mlc-llm icon mlc-llm

Enable everyone to develop, optimize and deploy AI models natively on everyone's devices.

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