Projects sharing features with Visu3d

This repository contains the code release for Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields. This implementation is written in JAX, and is a fork of Google's JaxNeRF implementation. Contact Jon Barron if you encounter any issues.

This repository serves as a comprehensive research platform and toolkit for advancing machine learning, quantum computing, and large-scale scientific data analysis. It provides foundational frameworks for developing complex algorithmic systems, offering the necessary infrastructure for distributed training, computational graph execution, and high-performance model development. The project distinguishes itself by integrating specialized research domains with robust, privacy-preserving methodologies. It supports diverse scientific discovery through tools for quantum simulation, physics-informed

btplotting provides plotting for backtests, optimization results and live data from backtrader.

Visualization of Motions for Legged Robots in ros-rviz

dtale is a web-based interactive grid and visualizer for pandas dataframes, designed as an exploratory data analysis tool. It provides a browser-based interface for analyzing tabular data structures, allowing users to calculate statistics, detect outliers, and compute correlations without writing manual code. The project functions as an embedded data viewer that can be integrated into web applications via iframes or custom routes, with specific support for Django, Flask, and Streamlit. It enables the exploration of datasets through a combination of an interactive data grid and a data visualiz

mplfinance is a financial time-series plotter and market data visualization framework built on Matplotlib. It is designed to render market data frames into specialized charts, including candlesticks, OHLC bars, Renko bricks, and point-and-figure columns. The library distinguishes itself through a dedicated market data framework that manages trading calendars and non-trading periods, ensuring accurate temporal spacing by collapsing gaps during holidays. It also provides a system for technical analysis charting, enabling the overlay of moving averages, volume bars, and other technical indicator

Portfolio and risk analytics in Python

Modular ROS visualization tool for 2D data.

Go Language Library for SVG generation

This project is a PyTorch implementation of a Neural Radiance Field framework. It serves as a 3D scene synthesizer and differentiable volumetric renderer used to train volumetric representations of scenes by predicting color and density for 3D spatial coordinates. The system enables novel view synthesis, allowing for the generation of new images of complex 3D scenes from previously unseen perspectives. It supports 3D scene reconstruction by processing 2D images and camera poses to build a digital volumetric representation of a physical space. The framework includes capabilities for 3D model

This project is a framework for neural radiance fields used to synthesize three-dimensional environments from sets of two-dimensional images and camera poses. It functions as a volumetric rendering engine and scene synthesizer that optimizes neural representations of spatial volumes to generate novel views of complex 3D scenes. The system implements a coordinate encoding system that transforms spatial coordinates into high-dimensional space to capture high-frequency geometric details. It also includes a neural mesh extractor that converts trained radiance fields into triangle meshes via march

PyTorch3D is a 3D geometric deep learning library and mesh processing toolkit designed for learning from point clouds and complex 3D surface geometries. It provides a collection of reusable components and data structures for deep learning with 3D data, including a framework for training and evaluating neural radiance fields to enable photorealistic view synthesis. The project features a differentiable 3D renderer that converts meshes and point clouds into 2D images while allowing gradients to flow back into the geometry and textures. This enables 3D shape optimization, where mesh geometry, te