CURL: Contrastive Unsupervised Representation Learning for Sample-Efficient Reinforcement Learning
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Updated
Oct 28, 2020 - Python
CURL: Contrastive Unsupervised Representation Learning for Sample-Efficient Reinforcement Learning
Generate a quantization parameter file for ncnn framework int8 inference
[ICLR 2025] Animate-X: Universal Character Image Animation with Enhanced Motion Representation
Social distance detection , a deep learning computer vision project with yolo object detection
Hands-on implementations of advanced deep learning architectures and techniques. Focused on real-world applications, optimization, and research-level concepts.
SentimentAnalysizer: An AI-powered app that analyzes text and instantly detects whether it expresses positive or negative sentiment.
This is the official implementation of EmoMusicTV (TMM).
The Oxynet Python package repository
Spatial Multiomics Profiler for Spatial Characterization of Tissue Microenvironment (https://smprofiler.io)
An AI-powered Smart Attendance System uses face recognition and liveness detection to automate attendance, ensuring accuracy, security, and real-time tracking.
Bird's tweet classification with Deep Learning
Ultra-Realistic Portrait Animation Studio Transform still portraits into lifelike, animated videos using the power of AI. PresentaPulse combines LivePortrait for sophisticated facial animation and Real-ESRGAN for video enhancement, all within a sleek, feature-packed desktop application.
Object detection et instance segmentation pour la compétition Copernicus Masters 2021 avec Mask R-CNN en TensorFlow2
Simple project to detect if a person is wearing a mask
This repository contains datasets for deep model training, AI-related competitions, websites for learning AI for free, online brush-ups, outsourcing websites, some tools you can use to do research, build, and some open-source tools.
Social distancing detection, a deep learning computer vision project with yolo object detection using python, OpenCV and YOLOv3 model.
Generate complete 3D scenes and environments from text descriptions using neural radiance fields and diffusion models - text-to-3D revolution.
This project is part of Kits19 challenge of grandchallenge. I had implemetated as in python using the U-Net and Autoencoder. It was done in Internship at Bennett University under LeadingIndia.ai project.
Implementation of Conditional Generative Adversarial Nets with PyTorch.
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